{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fetch data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os \n",
    "import pandas as pd \n",
    "def load_housing_data(path = './'):\n",
    "    csv_path = os.path.join(path, 'housing.csv')\n",
    "    return pd.read_csv(csv_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.88</td>\n",
       "      <td>41.0</td>\n",
       "      <td>880.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>322.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>8.3252</td>\n",
       "      <td>452600.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.86</td>\n",
       "      <td>21.0</td>\n",
       "      <td>7099.0</td>\n",
       "      <td>1106.0</td>\n",
       "      <td>2401.0</td>\n",
       "      <td>1138.0</td>\n",
       "      <td>8.3014</td>\n",
       "      <td>358500.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-122.24</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1467.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>496.0</td>\n",
       "      <td>177.0</td>\n",
       "      <td>7.2574</td>\n",
       "      <td>352100.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1274.0</td>\n",
       "      <td>235.0</td>\n",
       "      <td>558.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>5.6431</td>\n",
       "      <td>341300.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1627.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>259.0</td>\n",
       "      <td>3.8462</td>\n",
       "      <td>342200.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "0    -122.23     37.88                41.0        880.0           129.0   \n",
       "1    -122.22     37.86                21.0       7099.0          1106.0   \n",
       "2    -122.24     37.85                52.0       1467.0           190.0   \n",
       "3    -122.25     37.85                52.0       1274.0           235.0   \n",
       "4    -122.25     37.85                52.0       1627.0           280.0   \n",
       "\n",
       "   population  households  median_income  median_house_value ocean_proximity  \n",
       "0       322.0       126.0         8.3252            452600.0        NEAR BAY  \n",
       "1      2401.0      1138.0         8.3014            358500.0        NEAR BAY  \n",
       "2       496.0       177.0         7.2574            352100.0        NEAR BAY  \n",
       "3       558.0       219.0         5.6431            341300.0        NEAR BAY  \n",
       "4       565.0       259.0         3.8462            342200.0        NEAR BAY  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing = load_housing_data()\n",
    "housing.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 20640 entries, 0 to 20639\n",
      "Data columns (total 10 columns):\n",
      "longitude             20640 non-null float64\n",
      "latitude              20640 non-null float64\n",
      "housing_median_age    20640 non-null float64\n",
      "total_rooms           20640 non-null float64\n",
      "total_bedrooms        20433 non-null float64\n",
      "population            20640 non-null float64\n",
      "households            20640 non-null float64\n",
      "median_income         20640 non-null float64\n",
      "median_house_value    20640 non-null float64\n",
      "ocean_proximity       20640 non-null object\n",
      "dtypes: float64(9), object(1)\n",
      "memory usage: 1.6+ MB\n"
     ]
    }
   ],
   "source": [
    "housing.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count         20640\n",
       "unique            5\n",
       "top       <1H OCEAN\n",
       "freq           9136\n",
       "Name: ocean_proximity, dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.ocean_proximity.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['NEAR BAY', '<1H OCEAN', 'INLAND', 'NEAR OCEAN', 'ISLAND'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.ocean_proximity.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<1H OCEAN     9136\n",
       "INLAND        6551\n",
       "NEAR OCEAN    2658\n",
       "NEAR BAY      2290\n",
       "ISLAND           5\n",
       "Name: ocean_proximity, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.ocean_proximity.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20433.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-119.569704</td>\n",
       "      <td>35.631861</td>\n",
       "      <td>28.639486</td>\n",
       "      <td>2635.763081</td>\n",
       "      <td>537.870553</td>\n",
       "      <td>1425.476744</td>\n",
       "      <td>499.539680</td>\n",
       "      <td>3.870671</td>\n",
       "      <td>206855.816909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.003532</td>\n",
       "      <td>2.135952</td>\n",
       "      <td>12.585558</td>\n",
       "      <td>2181.615252</td>\n",
       "      <td>421.385070</td>\n",
       "      <td>1132.462122</td>\n",
       "      <td>382.329753</td>\n",
       "      <td>1.899822</td>\n",
       "      <td>115395.615874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-124.350000</td>\n",
       "      <td>32.540000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.499900</td>\n",
       "      <td>14999.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-121.800000</td>\n",
       "      <td>33.930000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>1447.750000</td>\n",
       "      <td>296.000000</td>\n",
       "      <td>787.000000</td>\n",
       "      <td>280.000000</td>\n",
       "      <td>2.563400</td>\n",
       "      <td>119600.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-118.490000</td>\n",
       "      <td>34.260000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>2127.000000</td>\n",
       "      <td>435.000000</td>\n",
       "      <td>1166.000000</td>\n",
       "      <td>409.000000</td>\n",
       "      <td>3.534800</td>\n",
       "      <td>179700.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>-118.010000</td>\n",
       "      <td>37.710000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>3148.000000</td>\n",
       "      <td>647.000000</td>\n",
       "      <td>1725.000000</td>\n",
       "      <td>605.000000</td>\n",
       "      <td>4.743250</td>\n",
       "      <td>264725.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>-114.310000</td>\n",
       "      <td>41.950000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>39320.000000</td>\n",
       "      <td>6445.000000</td>\n",
       "      <td>35682.000000</td>\n",
       "      <td>6082.000000</td>\n",
       "      <td>15.000100</td>\n",
       "      <td>500001.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          longitude      latitude  housing_median_age   total_rooms  \\\n",
       "count  20640.000000  20640.000000        20640.000000  20640.000000   \n",
       "mean    -119.569704     35.631861           28.639486   2635.763081   \n",
       "std        2.003532      2.135952           12.585558   2181.615252   \n",
       "min     -124.350000     32.540000            1.000000      2.000000   \n",
       "25%     -121.800000     33.930000           18.000000   1447.750000   \n",
       "50%     -118.490000     34.260000           29.000000   2127.000000   \n",
       "75%     -118.010000     37.710000           37.000000   3148.000000   \n",
       "max     -114.310000     41.950000           52.000000  39320.000000   \n",
       "\n",
       "       total_bedrooms    population    households  median_income  \\\n",
       "count    20433.000000  20640.000000  20640.000000   20640.000000   \n",
       "mean       537.870553   1425.476744    499.539680       3.870671   \n",
       "std        421.385070   1132.462122    382.329753       1.899822   \n",
       "min          1.000000      3.000000      1.000000       0.499900   \n",
       "25%        296.000000    787.000000    280.000000       2.563400   \n",
       "50%        435.000000   1166.000000    409.000000       3.534800   \n",
       "75%        647.000000   1725.000000    605.000000       4.743250   \n",
       "max       6445.000000  35682.000000   6082.000000      15.000100   \n",
       "\n",
       "       median_house_value  \n",
       "count        20640.000000  \n",
       "mean        206855.816909  \n",
       "std         115395.615874  \n",
       "min          14999.000000  \n",
       "25%         119600.000000  \n",
       "50%         179700.000000  \n",
       "75%         264725.000000  \n",
       "max         500001.000000  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt \n",
    "housing.hist(figsize=(20,15), bins = 50)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# median age and house value has maximun value "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as  np \n",
    "def split_train_test(data, ratio = 0.1): \n",
    "    randomOrder = np.random.permutation(len(data))\n",
    "    test_len = int(len(data) * ratio)\n",
    "    train_indexes = randomOrder[test_len:]\n",
    "    test_indices = randomOrder[:test_len]\n",
    "    return data.iloc[train_indexes], data.iloc[test_indices]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_set, test_set = split_train_test(housing,0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16512"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(train_set)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import hashlib\n",
    "def is_in_test_set(identifier, ratio=0.1, hash = hashlib.md5):\n",
    "    return hash(np.int64(identifier)).digest()[-1] < 256 * ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def split_train_test_set(data, id_colum,ratio = 0.1):\n",
    "    ids = data[id_colum]\n",
    "    in_test_set = ids.apply(lambda id_: is_in_test_set(id_, ratio))\n",
    "    return data.loc[-in_test_set], data.loc[in_test_set]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "housing_with_id = housing.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_set, test_set = split_train_test_set(housing_with_id, 'index')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.88</td>\n",
       "      <td>41.0</td>\n",
       "      <td>880.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>322.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>8.3252</td>\n",
       "      <td>452600.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.86</td>\n",
       "      <td>21.0</td>\n",
       "      <td>7099.0</td>\n",
       "      <td>1106.0</td>\n",
       "      <td>2401.0</td>\n",
       "      <td>1138.0</td>\n",
       "      <td>8.3014</td>\n",
       "      <td>358500.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>-122.24</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1467.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>496.0</td>\n",
       "      <td>177.0</td>\n",
       "      <td>7.2574</td>\n",
       "      <td>352100.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1274.0</td>\n",
       "      <td>235.0</td>\n",
       "      <td>558.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>5.6431</td>\n",
       "      <td>341300.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.84</td>\n",
       "      <td>52.0</td>\n",
       "      <td>2535.0</td>\n",
       "      <td>489.0</td>\n",
       "      <td>1094.0</td>\n",
       "      <td>514.0</td>\n",
       "      <td>3.6591</td>\n",
       "      <td>299200.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index  longitude  latitude  housing_median_age  total_rooms  \\\n",
       "0      0    -122.23     37.88                41.0        880.0   \n",
       "1      1    -122.22     37.86                21.0       7099.0   \n",
       "2      2    -122.24     37.85                52.0       1467.0   \n",
       "3      3    -122.25     37.85                52.0       1274.0   \n",
       "6      6    -122.25     37.84                52.0       2535.0   \n",
       "\n",
       "   total_bedrooms  population  households  median_income  median_house_value  \\\n",
       "0           129.0       322.0       126.0         8.3252            452600.0   \n",
       "1          1106.0      2401.0      1138.0         8.3014            358500.0   \n",
       "2           190.0       496.0       177.0         7.2574            352100.0   \n",
       "3           235.0       558.0       219.0         5.6431            341300.0   \n",
       "6           489.0      1094.0       514.0         3.6591            299200.0   \n",
       "\n",
       "  ocean_proximity  \n",
       "0        NEAR BAY  \n",
       "1        NEAR BAY  \n",
       "2        NEAR BAY  \n",
       "3        NEAR BAY  \n",
       "6        NEAR BAY  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_set.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# use log and lat to generate the unique index\n",
    "housing_with_id['id'] = housing['longitude'] * 360 + housing['latitude']\n",
    "train_set, test_set = split_train_test_set(housing_with_id, 'id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.88</td>\n",
       "      <td>41.0</td>\n",
       "      <td>880.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>322.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>8.3252</td>\n",
       "      <td>452600.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>-43964.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.86</td>\n",
       "      <td>21.0</td>\n",
       "      <td>7099.0</td>\n",
       "      <td>1106.0</td>\n",
       "      <td>2401.0</td>\n",
       "      <td>1138.0</td>\n",
       "      <td>8.3014</td>\n",
       "      <td>358500.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>-43961.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>-122.24</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1467.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>496.0</td>\n",
       "      <td>177.0</td>\n",
       "      <td>7.2574</td>\n",
       "      <td>352100.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>-43968.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1274.0</td>\n",
       "      <td>235.0</td>\n",
       "      <td>558.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>5.6431</td>\n",
       "      <td>341300.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>-43972.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1627.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>259.0</td>\n",
       "      <td>3.8462</td>\n",
       "      <td>342200.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>-43972.15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index  longitude  latitude  housing_median_age  total_rooms  \\\n",
       "0      0    -122.23     37.88                41.0        880.0   \n",
       "1      1    -122.22     37.86                21.0       7099.0   \n",
       "2      2    -122.24     37.85                52.0       1467.0   \n",
       "3      3    -122.25     37.85                52.0       1274.0   \n",
       "4      4    -122.25     37.85                52.0       1627.0   \n",
       "\n",
       "   total_bedrooms  population  households  median_income  median_house_value  \\\n",
       "0           129.0       322.0       126.0         8.3252            452600.0   \n",
       "1          1106.0      2401.0      1138.0         8.3014            358500.0   \n",
       "2           190.0       496.0       177.0         7.2574            352100.0   \n",
       "3           235.0       558.0       219.0         5.6431            341300.0   \n",
       "4           280.0       565.0       259.0         3.8462            342200.0   \n",
       "\n",
       "  ocean_proximity        id  \n",
       "0        NEAR BAY -43964.92  \n",
       "1        NEAR BAY -43961.34  \n",
       "2        NEAR BAY -43968.55  \n",
       "3        NEAR BAY -43972.15  \n",
       "4        NEAR BAY -43972.15  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_set.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "train_set, test_set = train_test_split(housing, test_size = 0.2, random_state = 42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14196</th>\n",
       "      <td>-117.03</td>\n",
       "      <td>32.71</td>\n",
       "      <td>33.0</td>\n",
       "      <td>3126.0</td>\n",
       "      <td>627.0</td>\n",
       "      <td>2300.0</td>\n",
       "      <td>623.0</td>\n",
       "      <td>3.2596</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8267</th>\n",
       "      <td>-118.16</td>\n",
       "      <td>33.77</td>\n",
       "      <td>49.0</td>\n",
       "      <td>3382.0</td>\n",
       "      <td>787.0</td>\n",
       "      <td>1314.0</td>\n",
       "      <td>756.0</td>\n",
       "      <td>3.8125</td>\n",
       "      <td>382100.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17445</th>\n",
       "      <td>-120.48</td>\n",
       "      <td>34.66</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1897.0</td>\n",
       "      <td>331.0</td>\n",
       "      <td>915.0</td>\n",
       "      <td>336.0</td>\n",
       "      <td>4.1563</td>\n",
       "      <td>172600.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14265</th>\n",
       "      <td>-117.11</td>\n",
       "      <td>32.69</td>\n",
       "      <td>36.0</td>\n",
       "      <td>1421.0</td>\n",
       "      <td>367.0</td>\n",
       "      <td>1418.0</td>\n",
       "      <td>355.0</td>\n",
       "      <td>1.9425</td>\n",
       "      <td>93400.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2271</th>\n",
       "      <td>-119.80</td>\n",
       "      <td>36.78</td>\n",
       "      <td>43.0</td>\n",
       "      <td>2382.0</td>\n",
       "      <td>431.0</td>\n",
       "      <td>874.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>3.5542</td>\n",
       "      <td>96500.0</td>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "14196    -117.03     32.71                33.0       3126.0           627.0   \n",
       "8267     -118.16     33.77                49.0       3382.0           787.0   \n",
       "17445    -120.48     34.66                 4.0       1897.0           331.0   \n",
       "14265    -117.11     32.69                36.0       1421.0           367.0   \n",
       "2271     -119.80     36.78                43.0       2382.0           431.0   \n",
       "\n",
       "       population  households  median_income  median_house_value  \\\n",
       "14196      2300.0       623.0         3.2596            103000.0   \n",
       "8267       1314.0       756.0         3.8125            382100.0   \n",
       "17445       915.0       336.0         4.1563            172600.0   \n",
       "14265      1418.0       355.0         1.9425             93400.0   \n",
       "2271        874.0       380.0         3.5542             96500.0   \n",
       "\n",
       "      ocean_proximity  \n",
       "14196      NEAR OCEAN  \n",
       "8267       NEAR OCEAN  \n",
       "17445      NEAR OCEAN  \n",
       "14265      NEAR OCEAN  \n",
       "2271           INLAND  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_set.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f47ad008850>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing['median_income'].hist(bins=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "    1. Catecories of incomes \n",
    "    2. Sliced the examples, each categories should have enough examples;\n",
    "    3. The median divides 1.5 to limites the number of categories."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "housing['income_cat'] = np.ceil(housing['median_income']/1.5)\n",
    "housing['income_cat'].where(housing['income_cat'] < 5, 5.0, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    20640.000000\n",
       "mean         3.006686\n",
       "std          1.054618\n",
       "min          1.000000\n",
       "25%          2.000000\n",
       "50%          3.000000\n",
       "75%          4.000000\n",
       "max          5.000000\n",
       "Name: income_cat, dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing['income_cat'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "housing['income_cat'] = pd.cut(housing['median_income'], bins = [0,1.5,3,4.5,6, np.inf], labels=[1,2,3,4,5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f47b7961430>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing['income_cat'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import StratifiedShuffleSplit\n",
    "split = StratifiedShuffleSplit(n_splits= 1, test_size=0.2, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "for train_index, test_index in split.split(housing, housing['income_cat']):\n",
    "    train_set = housing.loc[train_index]\n",
    "    test_set = housing.loc[test_index]    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(16512, 11)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_set.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "      <th>income_cat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17606</th>\n",
       "      <td>-121.89</td>\n",
       "      <td>37.29</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1568.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>710.0</td>\n",
       "      <td>339.0</td>\n",
       "      <td>2.7042</td>\n",
       "      <td>286600.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18632</th>\n",
       "      <td>-121.93</td>\n",
       "      <td>37.05</td>\n",
       "      <td>14.0</td>\n",
       "      <td>679.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>306.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>6.4214</td>\n",
       "      <td>340600.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14650</th>\n",
       "      <td>-117.20</td>\n",
       "      <td>32.77</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1952.0</td>\n",
       "      <td>471.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>462.0</td>\n",
       "      <td>2.8621</td>\n",
       "      <td>196900.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3230</th>\n",
       "      <td>-119.61</td>\n",
       "      <td>36.31</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1847.0</td>\n",
       "      <td>371.0</td>\n",
       "      <td>1460.0</td>\n",
       "      <td>353.0</td>\n",
       "      <td>1.8839</td>\n",
       "      <td>46300.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3555</th>\n",
       "      <td>-118.59</td>\n",
       "      <td>34.23</td>\n",
       "      <td>17.0</td>\n",
       "      <td>6592.0</td>\n",
       "      <td>1525.0</td>\n",
       "      <td>4459.0</td>\n",
       "      <td>1463.0</td>\n",
       "      <td>3.0347</td>\n",
       "      <td>254500.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "17606    -121.89     37.29                38.0       1568.0           351.0   \n",
       "18632    -121.93     37.05                14.0        679.0           108.0   \n",
       "14650    -117.20     32.77                31.0       1952.0           471.0   \n",
       "3230     -119.61     36.31                25.0       1847.0           371.0   \n",
       "3555     -118.59     34.23                17.0       6592.0          1525.0   \n",
       "\n",
       "       population  households  median_income  median_house_value  \\\n",
       "17606       710.0       339.0         2.7042            286600.0   \n",
       "18632       306.0       113.0         6.4214            340600.0   \n",
       "14650       936.0       462.0         2.8621            196900.0   \n",
       "3230       1460.0       353.0         1.8839             46300.0   \n",
       "3555       4459.0      1463.0         3.0347            254500.0   \n",
       "\n",
       "      ocean_proximity income_cat  \n",
       "17606       <1H OCEAN          2  \n",
       "18632       <1H OCEAN          5  \n",
       "14650      NEAR OCEAN          2  \n",
       "3230           INLAND          2  \n",
       "3555        <1H OCEAN          3  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_set.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "train_set.hist(figsize=(20,15))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3    0.280475\n",
       "2    0.255087\n",
       "4    0.141037\n",
       "5    0.091521\n",
       "1    0.031880\n",
       "Name: income_cat, dtype: float64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_set.income_cat.value_counts()/len(housing)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3    0.350581\n",
       "2    0.318847\n",
       "4    0.176308\n",
       "5    0.114438\n",
       "1    0.039826\n",
       "Name: income_cat, dtype: float64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.income_cat.value_counts()/len(housing)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualise Geographical Data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f47b89f0dc0>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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j/RMS638iazJN3qmpRwPHM4BfFwhNMK28mMlzV+PRRNo+jFQIIaLvH/mcklmvbmLFx3vxOOQqAs2LDsbJj9sT8ZnoEdkT9/afrcfiHbAuBCu37OW8Ef1aJW+hUCgidMocg303mUo/KBV2IzNtbHHMc/ZksEVj0EjMKUh49B8fE3SY0Gbh0QR3fGu4Y65CCsEL15/BgopajoZMGgLZfRYLp0lxyzZ9nnDvAp+OTxd08cZ+HmlKLn1qddbjMlON23RywI1Bg/sWVzP+oRXMX7sjJvegSlYVivzRKR2DUwNUplhGpr4hwIL1sfX8VjLYjpOhOho2E4T64gmGDa4aN4Tf/9vXE8Z1enXBqm37HGdCZ8OU0hPTvqbAr3P/lFEsu+2chOcCRuT0kM24zHTjNu3NcFYVFUQaDY+GTO55dRNX/34t3/jVWzz11jb2NwaZeFq/mPdwctgKhSJzOqVjyESO2gm/R0STo5l02d5ybgm+9KOYYxGCNTX7GDWwByaxTqQxYPCH1dsdTz3dfJn/6i74yoCEjuV4woZJvx5+ehf4YrqWnU4QmXQbu/kerdnO0y86zfEeDQGDQFjy2JtbueDXq1i26fOY550ctkKhyJxO6RichsxPKT0Rjy7o5tNIVfrfzafz7HXl0Y7kg03BhIqd+JCFFSJ5ZtV2QOB1CAslw+pOBo7tmP3HvEujLUFS4NPp4tV44Luj+euNZ/HvZw11/T4Ah4+GeGRq7Pdy3VlDoj97tEh56y3zP2T8QysAotIVTieIVCWnq7Z+waqte6nZc5iqXQcIhY2ExPkRW4+FxeqafTy47KOMPpeFksVQKHJDp00+26tgNu0+yJylm+niiSh7/uziETHCcHZMKRk1sGdMKaQpwaNBV6+HoGHEDJ1xqo6Jx5rjbCaJKlkGzVrzyi17mf16dcxJocCvc/9lo2ISscW9u/LCup2Ek904jkDY4PvjhiZUB91+/nCq6w5x47wKAmEz2s1tjRy1Snfdlpze+VJlTJJc1yJd4fEYEiY99Q6PTC2NOuKWdKjbw3+q8U2hyJ5OeWKwsBqgrMEwljDe48u38svvjMani+jpwe8R+HTBrEkjAWLi4SFDomsa15w5BBA8s2p7NHnqFCKx7mXtyu+7bBTeFM1u9p13UaGf80b0w0iYFicTqnOKCv3cP2WU6+/jX3sbotfZBfkist3ehCa3ZKGeZOJ39Q0BfrqgMqFyKkXunUBYRnMNLckN+T0aD18+htU1+5ImuBUKhTs67YnBIllZ4+hBPXnv7vOp3d/E2u31PPbmVnwewZylm/myMZhwjUcT/GHNpxHFVVv55pJbz3YQzZP8/JIRjBtWRHHvrlTXHXJMIHfz6phIx/kKsaMxY08pdkYP6kmhX3dVsfT8ul18dvAoD00tzWpOs7W2ZLvw6rqDaeU9nLAcUDa5IY8G3ysfwn+MP4neBb7odDnV26BQZE+nPjFAaoNnnSh+vXwrwbAZrYCZu3JbQjy8KWgQl3vFq2k0Bo3oKcPO48u3Uty7K6tr9nHjvIqE2Q1+j8bvrh2bVHba2p3fOGEY8aeUhM+Xaksex/ItXzDuweXMX7cj5vH4qiDr9JSZQc2ueqohEI7+Ph6+fAx+j6CbV8erCUYO6E6yfLkuIkqvr1fVMXnuav6ybqeS41YockCndwxOiWhrh251Rsc3d3ma8wp2TGITwXDMwVi7dju6EFTXHWTmyxsTRoP6PYJHpo6JjhBNhaVKmqxEtKjQz63nJY7UTEXYhHte2cT8tbHOYUrZIGZNGknIlPg8GnOWbk5wRKm0jEYN7JHUiKdCAvsbg9G/Q6RFXNMEN597Cut+fgE//dbwmPkXHi3yvP27mbtyW0LPiOptUCgyJ++hJCGEDlQAu6WUk4UQJwMvAkXAeuBaKWUwn2twkmOwd0bHl4MGw4ZjYtqiwKdjyNgQUHwCuDFo8N6/6hNCUt18Or+75nQmDI+twXfCbXfvJaMHZKwHBXDf65u4ePQx/aP6hgBzlm4mGDaxDkz2UEw6baKiQj+PTyvjroWVZNpX+Mc1n3LnhcMTHKmVAP/J+ady1bgh0RGjEKmessue+3SdmyYM4+m3a5Qct0LRAlrjxHA7YK8/fAj4tZSyBNgP/KAV1hCTcE3WGV3gj5SD3nDOsJT3mn7RaTEhoKJCv2M46bk1nyaUulpVT25wG/ePdF1nHsYJmfCXdcf0kVL1Gjg1qE1fVJVwcphSNojZl42O2d0L0geZXvxgJ9V1B1OGgooK/UwY3pcJw/sxamBPx+/mqnFDWjQdTqFQ5NkxCCGKgUnA75t/FsBEYFHzS/4MfCefa3DCyQAW+CLloGtmTuSGc4al7EUY1rcgYRfqFE7y6Rq3nneqYxjLDcnCYECCPIRIM5chGU+t2OZKZsLpOwuEZYxjgWOnDntlks8jePOOCcy7/gzmXf91zjy5d8I6DAkrPtrrWuYiVYgwfhPgVsZboVBEyHco6TfADKB7889FwAEppXX+rwUct3RCiJuAmwCGDBmS00UlG1JvLwd97IpS7lpYlVBTr2swsKfzzIH4cJK1g71q3JCs6+rjw2BWOWZ8OCe+ismaFpeOoBEx7j85/9SYaihdE4QMyazJxxLQ9qE8FnNX1nDVuCExAnkJYniaRt3BJiYM78drlbtZ98l+x7XMe28HU5sVaS1SyVykU2xVstwKRXbk7cQghJgM7JVSrs/meinlM1LKcilled++fXO6tlS7TYspZYNYdts5XH3GEHz6sW5mr64xee7qhKSsm3u2ZL1Wk1kyvSF7j8Gz15VnVB80d2VNtEN5fEmfSAI6bOLVBL9YXM1Tb23j5fW1jnkDjyZiqn6cnO6RoMGN8yqYv24HMxZVJc3fmMCrH8Z+r04yF9YpoGbPYVcy3tloOykUxzP5PDGMB6YIIS4FugA9gCeAXkIIT/OpoRhokw6kTHabQgiM5moXS1I7vj6+viHA0KICltx6dows9WuVu5mxqApdaBjSjHb5ZkO6ZLT1p2bP4Yy7hy958h00IQiGTYSISGNY+ZFUie3GoMGmuoNRx2U5yOmLYpPIgbDk/sWbmyfWJV9bXF8f0pRRx1Ndd4gVH33O/Pd3gZSETKL6TfGngeq6Q2hx7lHJcisU7sibY5BS3g3cDSCEOBe4S0p5tRBiITCVSGXSvwGv5WsN6UjWrOVK5sJmZJxCFqWDe0U7gSP2MWJk73ipkl7dfIwa2MOVgbLLO2SSjPY0T4lzwzEDHnl9vHFOx/2vVzPupBMo6R+JGE4pG0Svbj5ufn59TP+GVxcEw8nLlQQQiltzwJCs+GgPT79d49g85+SoI844sUxYla4qFO5oiz6GmcCdQogaIjmHP7TBGlLiRprBmqq2autepi+sdAxZVNcdSjBmhoQfzqtwJdcQP79gTc2+lOEqK8QSChuunUIuCBqROQ32z+OkFmuYku8mOS15NLjzW8MTFFwBnljh7BTsWI664pN6frqg0rF3RJWuKhTuaBVJDCnl28DbzX/fDpzRGu+bLU47c2+zrpJP1wmZJtPGRqaqGaYkrqnZVmLpbJybws7hKDvJRleumTmRNTMnJoTA7KeWeKPYGgRtU+8g4lxnTR7JnCXHZkxbP9vx6oJfTyvlrFMi1z39dk1W7x8yTeav2xGTuLbIpHdEoVAcB1pJ2ZBseL2Vkyjw6UyeuzoaxognaBjR0I9XF0mrg1LFvFPlE+wCeOAu9NUa6EIwf91O/sfWYDZr0khGD+oZU/JqX2MXj87gE46V/04bW8y8tTuTvYUjfo/GnRcM58E3tjg+bzQ7+fqGgDoxKBQuUI4hCcmS00WFfqp2HUgwcHZuPe/UmLLX6Ys2ogloCrmPeWcyutLJ4LYFjUGDJ9/aStgkupb7F1ez7LZzot9HouCgEZ3J4DQtLx1XnzGEOy8czsotex2f1zg2Y0KVrCoU7uj0WkktoajQT4FPZ+WWyMAZi1QqoH6PxlXjhkTj/eNL+vDuzyby4k1n8cB3RrsuZ01X/mpv3HJaT5b9bi0mPopl5R/mr90RCS9NGkkXrxbt1NY0ES3/TZbb8emCn186gvieQ13AnRcOp6jQT1lzVVQ8uhbp51AlqwqFe9SJIQn1DQFmLqpi+ZYvoo9d+tX+zPn2V4HIGM+5K7eBjFTOWEnTWZNG8uw723l21faI1LaQPHpFGVPKBlE6uBcXjx6Qsvbe/lyyU4tTFVR8g1uqwUCtTTAcmdlc6NcJm5I7LxjOo29uBWRMVZGThLnPo7HsJ2fTu8DHI3//GMMWltNs3q93gS+hEFYAPo9OyNaAoUpWFYr0KMfggNMUMoBl/9zDP6r3ApKuXg8guHViCZeMHhCp5999kHtf2xS9zhq2c/uLldEkc7IS2WRduvGvd5OUPtgU5IY/fZCPr6ZFWDMjHn1zK15NYFdOtCTMrR4IXYtMvXtk6hhK+nenatcBunj0GNG8Lh49auRr9zdR6PdwOHDs+W5+naAqWVUoMkaFkuKobwg4OgWLsCkJm3A4ECYQNnn67Rp6F/go7t2VXyypdrxOAi++vzMawojX78mkSzeV0J3VIT1qYM+k60+HLwsxvkzRheBoXD/D0XAkYd/cSdG89T/2IZLlXAp8OlW7DlDg0xMkt48EjZjEv1dXJasKhRvUiSGO6rpDGRlVu/qnSHHdr5dv5ckV2/h22UBe2bAbXdOQSB6ZWsrQogJX8trgbCCDRuwuuKjQz8yLRySt0kmG39M6pa5N8fW9gGlK9jcGm2W3JVZDoL2kN75SbFp5pGTYSTodEhv1QoaMltMqFIrkqBNDApltta3QRMRgJ782bEZkIRZU7CZkwtGwSSAsuXNBJQU+PWNVUbv6q2GarKnZF/O6m755CtPKizP6LG3R/2BhSHj07x8nDE3yahrVdYeiiXxLD2rJrWezoKI2QTo9Hf/1yj9V8lmhSINyDHGMGtgzpeS2HXs3bVGhn2vPHJrx+4VNqDt4lGljY414KlXR8SV9YqqOwiaOoaeZF4/Ap9Nh+NvmPQmzq5tCYW6cVxHT/V06uBeNQcNxjnY63qjew9hfLk/bda5QHM8oxxBHUaGfx64oTTuisptP59nryhlf0ieaL7gmC8cAcKgplFC//9IHu5LmJGr3N+HTYy2+02zj2v1N+DwdyDPYKPDr+D0CIYTjaNNMZ13H89OFiUOGFApFBJVjcGBK2SBGntiDi594J6nmkCklu75s4qbn10dj3recW0IXr5a0I9oJAfTo6k24JhCWPLh0M6cPPYE5SzcndGDHT4azQk/2ktdNuw8m7MA7AgU+nekXngZIHv3HVkJGYrlp6eBezL5sFPe8uimr9zAlqmxVoUiCkJlKabYB5eXlsqKiotXf9/XK3Y7DegB+fskIHl++Ncag+z0aIJuTp+4Z3q+ArXsbXb3W7xHcO3kU9y2ujlbceDR4fFoZEqIlr5kM62lvaIDXo+HREpPKXbwaa2ZOjBr0+et2cP/izUgpM/qsXl2w9u7zlWNQdGqEEOullOWZXqdCSSmYUjaI3/9bOd3iAvUFfp0TCnwJZaM+XeP68Sdn/D5unQJEThL3vrYpxgjqmsbIE3vElLwGwpkZynaFiCTCneZxx5ebXj1uKO/9bCJ/+LevJySuU/HYFaXKKSgUSVCOIQ2jBvbEjDtVGaakbHAvx0qiIxlUyGRLvL33aILKZv2mTkHc57PP43bSOSoq9DNheF+uOdPdCNjS4u58uHN/jMyJQqE4RiexJPnDrllU4NPx6YJZk0ZS0r87D18+Br9Ho5tPx+/RmDLmRP783o5WX2Nj0GDXl0cSHJVHs8JbHYv4DE38PG4n6hsCTBzR39X9q2oP88d3d3DBr1dx72v/bMFKFYrOScezGm3AlLJBkTnIpsTn0ZizdDOvV+6O6dKV0uTlD9uuBPKJFTVMKR0YI7r3+LQynr2uHG+GinrtyZfEdyvHV2jBsYFGt8zfkCC0l4557+1UJweFIg5VleSC+oYAc5ZuJhg2CTZL8dy1sAqJNaQnefjIqwumX3Qav1q2Je+i2K9W1rHsJ7Ezpys+qU/ZeBePV8u0xS+/mOaxbmUnPanxJX1aPIvilQ9rmX7xV3K5bIWiQ6Mcgwuc5h04VSo5cXi+cZcAACAASURBVN+UUVw9bigjBnTnh8+vT5jJkEu8eqSKp7RZgvq1yt1MX1iV0T1MIuJ17QVDwv/+37/Ye/goS6o+IyyJEQ985tqxicN/vBohw8Rtm8PBpnD6FykUxxHtKGjQfkk1f8GOFdO3chEPfGc0V4+LNL2NGtgz7zvxsE0zyRLmc+vALNqTU7B45p1PeLUy4hTsRJLtIqGnA+ClG8903cH+nbKBOVilQtF5UI7BBfYEdDevcyexR4P7p4zm3Z9N5C83nsl7d5/P1c2d0FbT2Z0XDM/rOq8ff3I0Fl9ddxDNQTLCqwvaaIZPzgmZJru+PBIzd8KjwcOXj6H85CJum3hq2nsMOaEL5ScXOeYuFIrjFRVKcok1NKe67hA3zqtIEJzze3TmLN1M9y6emJJKe1w8YJj4dUEgT/0FZ51SFH3PGYuqEhrtfLpg/ClFrNy6z+nyDseV5YP5xZLNCT0dVk7iqnFDeGpFTYIct509hwLMX7sjobtcjf9UHM+oE0MGWPXyj0w9Vr5q0Rg0EuYoxM9ZCIbNvDkFgC8bAtH3jHcKfo/GXRee1mmcAsBfP9iV4KB9+jHNqKJCP7OnjEx5D4+ucf/ialezMBSK4wV1YsgC6/Swcste7ltcHaNHZJ+j4JS07uLVME1JJDae20T0fy7YyAVf6ZfwngDXjz+JEwp8OX2/tsZJJjxgmDEO++pxQ0HC/Yur0TWRkPwPGRKvrsXkKVKN/4wfv6pQdEbUiSFLigr9nDeiX4LInn2OQnHvrjSFYitewobJstvO4ff/Njbjmns3LP9oLw2BxCqb36/+hN7dvLl/w1ZGT/L/WF/zE0JKJs9dHSOrffWZQ5l92SgMU+L3RL50vy7o4tWYfdnI6AhWi/hZGFb+Yf7aHYx/aEVUAlxJdys6K+rE0AKcporFa/kIETuiXghB7wIfK7bszXr8ZjqcbhsyJDfP35CfN2xFDDMiAWJ3yD5dIJtPSAFDgiG5a2EVI0/sQUn/7sf6UGxfuBSCpbeeTUn/7nT3e5L+Dq0ckX1KnL1c1poup1B0JpRjaCFWWMkpvFC7v8lxgP3v39nOb/9ve6uvtcOK6sURf0r71lf6s2rbvpjvOWhILn1qNY9OHeM4OtWva1FDn+x3aM8ROZEq5KRQdGRUKCkHFBX6KR3cy+V8ZoNn3vmkNZfX6Xnzoz2OvQzBcCSR7GZ0qtPv0MoRJSPZ+FWFoqOjHEMesfc/WPpF148/uV02kXVkgobkghH9HTWevFrkZBD/e4gP+TmRrLExmQS4QtFZUKGkPBMfpqiuO9QmYaTOztJNnzs+bu3qSwf3ShryS4ZTDmnWpJGMHtQzeg9VpaTojCjH0AoUFfqjRmPUwB54NHCotFTkGL/n2K4+WwOeKofkJOqnGuMUnQEVSmpligr9PD6tDG8H++bzUVqbb+6+ZARTygZFZbmzLTN1yj/ENy+qxjhFZ6KDmafOwZSyQaz9+QV8Y9gJbb0U13TEgqbRA3uwausXzFiUewPulJi2qpQUio6OcgxtRFGhn6euOh2fsyZfm5HJ3OT2zKBefq7+w/vc/Pz6hA7pXBhwp8S0qlJSdBby5hiEEF2EEO8LIaqEENVCiPubHz9fCLFBCFEphFgthCjJ1xraO0WFfh69oiyi2tpOPER8j0BHZfeBAIGwyZFQYhlrLgy4U8VZqiolpd6q6EjkM/kcACZKKRuEEF5gtRDiDeC3wLellB8JIX4M/Bfw73lcR7tmStkgDh8NM3txdVsvpV0S3+XcErr5dEwpc1ZmmioxbUclqRUdjbw5BimlBBqaf/Q2/5HNf3o0P94TqMvXGjoCllxDuCMG8XOMrpEwdU2I3Hwvfo/gd9eczqiBPTNyCumqmewVZ8mujx89qqQ0FO0dV45BCDGcyE6/v5RytBBiDDBFSvnLNNfpwHqgBHhaSrlOCHEDsEwI0QQcAs5Mcu1NwE0AQ4YMcft5OhxOCqzHI7om8OoCwzTx6SKqa+QQCcqK7319MBOG9wPcK6TmYqfv9PtVUhqK9o7bHMOzwN1ACEBKuRG4Mt1FUkpDSlkGFANnCCFGA3cAl0opi4E/Ao8nufYZKWW5lLK8b9++LpfZ8XA7NrSzY5gyqklkSkm3HNfzLqiopb4h4Lp0NRflqPUNAQ42BRPkOlSSWtHecfuvr5uU8v24x1xPUJdSHgBWApcApVLKdc1PvQR8w+19OiNOScwHvjuaedefwfQL8zsKtL0SNkkQrvN7NP77u6PxZFk05dU0qusOuTb2TuWouiZcVzO9Vrmbb/zqLW5+fgOGKfFoZCTHoVC0JW5zDPuEEKfQrOgshJgKfJbqAiFEXyAkpTwghOgKfAt4COgphBgupdza/NhHWa++k+A2iXk8YXcLHg0emRoJ43z02SHmrd2Z8f2Chsn2LxoSynGThXWcTnKNAYNNuw9SOrhXyveqbwjw0wWVzd3tkdOCLuDpq09n1MAe6veraPe4PTHcAvwvMEIIsRv4T+BHaa45EVgphNgIfAC8KaVcAtwIvCyEqAKuBaZntfJOhlN3rSWfcbwjhGDkiT2o2XOYFytqM75eE2CYJo/8/eOYaXsQCesU+PSEUtKiQj+zJieOBZ2zdHPacFJ13aEEyROrtiBbp6DKXRWtiasTg5RyO3CBEKIA0KSUh11csxH4msPjrwCvZLrQ4xFLPmP6oioAQmF5XKaoQ4bk4ifeQUqZtANbEzC4d1d2fOkQ6pEQlhAOHnMKBX4dw5RMKy9m8tzVCQnm+oYAfl2jm1fjSCjTxLHzIn/60odcdcZg7rjoK24+dhRV7qpobVI6BiHEnUkeB0BK6Zg4VuSO+DDTo3/fwl8/yHzX3NFJ1suga4Jrxg3hxQ928mVjiNh5eRHinWmBT+f+y0ZRNrgXk556h0BYxpSSHj4aZs7SzXg0EeMUwF3ieNTAnnh1kTAY6YvGEE+s3M7/vL2dbf89Kfp4qiopVe6qaAvSBSq6N/8pJxI6GtT852bg9PwuTWGRbBCQApCSFz/YSSAsORwIJ9mrxxI0TM4b0Y9lmz4nEI69QheC+5ds5mjIjAk7Ffjcz2AoKvTz2BWl+JIoD4Yk/PrvkdRauioppcmkaAtSnhiklJaMxSrgdCuEJIS4D1ia99UpEugs4zlzhd+rNx8R3Dc8GKakcud+nlqxLeG5oGHg9+gEbTV3Bf7ICeO8Ef1cO+cpZYPo1c3Ldc994Pj8axs/57rxw9KeBpQmk6ItcJva7A8EbT8Hmx9TtDLlQ3u39RIc6dmlbbSeQoaJIVNnXvxxO3dTwg/mrXd0sl8r7p3wuGHKjJyCxaiBPZM+9+0xA1ydBjLVZFIocoFbxzAPeF8IcV/zaWEd8Oe8rUqRlPKTWleqe9SAAn5+yYioYfLpEekKO36Pxo/PO7VV12UhpeTeyaOSChF282oZJezf37GfsGHi0QTdfDo+j8asySOzMsRFhX6evLIs4XGvgDsu+krS00B8ldSUskG8cP0Z/Mf4k3j6+19jaFGBqk5S5BURkTRy8UIhTgfOaf5xlZTyw7ytKo7y8nJZUVHRWm/XrqnadYCpv1uTM6mIdNx49sncM3kk9Q0B5q/bydMraxAi0oDm1wVCE8yaNJI5SzcnNKW1BgU+nb/ceCYFPp3VNV/w4LKPsBUf0cWrceXXB/Ond3dkdX+vAE3XuPW8Eq4aNyQrB1HfEOBXyz5i3af1fLd0YExV0uuVu2NGh04rL2ZBRW1MBVLFp1/G9G7oAjy64JGppdHqJDViVOGEEGK9lLI84+vcOAYhhKNYkZQy806jLFCO4Rj1DQG+8au3EpKm+eTMk3vz9NVjGf/Qihjj7/NoLPvJ2TQGDa75/ToOB1w3w+eU8qE92bDjILoWCRMJAV29noihHVvMSxW1CTMZssGrwX1TRnP1mUNzsOpjWEa9wKczee7q2O/YphsVj0eDdT+/gNU1+1Q5q8KRbB2D21DSUmBJ85+3gO3AG5m+maLlFBX6eWRqaas2vq39ZD9vVn+eEA/36xqNQYPi3l0T9IBak4odBzGBkBlpJAubkS7jJbeezYL1uXEKNN//nlc3MX+d8+kj2yY0q+qsMWgkfMdWabgTYRPe+9c+NWJUkXNcmRcp5VellGOa/5wKnAG8l9+lKZIxpWwQ635+AfOuP4NzTilqlfd8ecOupGJwRYV+bnXIMfh0jbaaB7fsn3WOhhZaPr969uvV1OyJ7fFs6VxpcK5ASnei39cQVOWsipyT1b5TSrkBGJfjtSgyoKjQz4ThfXn+xjNZfseEFhu7dFTsOBgzM8KjEVMdc9W4IfjjjjGaBgt/eGabjAt98YNa1m2vTzC0fo+G03IyWWLYkFz61Oqo8XerxJruROFUgTT7slFJ16GLyFxrVc6qyDVu5zHYO6A1Is1tx/WAnfZE7wIfmiYw8tjjICFGjkIIwfiSPtGfIyGuMTGJ1IcvH0P5yUXMuPg0Hly2Je176JrgitMHZaWH5MQj//iY6RedxuNvbo2u6ZZzS3hm1XZCcfmQTIfEBcMm0xdtpFc3H4eaQsSfjeKlM9zKWsR3utfub6K73+OYv/F6NK557n3HhLVKQCtaglt11e62v4eJ5Bxezv1yFNlQu7+JLh6dkNF6yd+QIamuO8iE4f2iydPxJX1YM3NiQnXMuJOL8OnEVAs5YZgSIWD5HRN4bs0n/OX9XS1e46N//5i7LjyNEwp8lA3uRe8CH3NXJja2ZUMgbPLvz73vWA5r37VnKmsRPxUu2bwOK0m9oKKWJbeeHc33KKegaCluHcNmKeVC+wNCiCuAhUler2hF2mrYz7KNn7H/SCjtTri4d9fmJGr6bflfP6jlrx/UOobGNBJ1j9IRNCQPvrEFvw4IwffKB2d8OkiF03r8HhGza2/JFDcrvGSdxAJhA00TMZVLXi1SBJBODlyhcIvbHMPdLh9TtAHxsWm/JzImM9+8WFHLXQur0sbWkyWnU+EUFevX3cfyOyZw8zeHZbzWgAGBsGTe2p1JZUW6+XT0FuZDuno1nr2uPMY5tlTWYkrZINbMnMgLN4xj2W3nJDzv9l5KulvhlnTqqpcAlwKDhBBP2p7qQQYT3BT5xx6bPtgU5Jb5H7ZKaCneyOqaYOWWvQkSEleNG8Jvlm9NKpvths8PB7n4N6sQeUhma8B5w/vwj817MlBdSsQwZYIURvyuP5s8gD28NG1scUzD27Ty4rT3UtLdikxIF0qqAyqAKcB62+OHicxuVrQjLONR3xBosznSjQGD2a9X81+vbUowPrlIkIfjs+A5wgSWbtrT4vvMvmyUo5HO1ZS++oYAC9bHJucXVNRy+/nDk95TSXcrMiWdumoVUCWEmC+lVCeEDoJ9h6ohONJa+hnNNDZnme3GxylB3s2rAyZHQh1TMdae89AF3PTNYVw8ekDS18cnlbMhm3xFS3IciuOTlDkGIcSC5r9+KITYGP+nFdanyBIrLv27a8cm9Be0FvZGK6c4u4nknZnn88spIzm5qBv9Cn0IMm+uaasmOvunMSQ8/96OtM1tLY3zZ5OvUNLdikxJqZUkhDhRSvmZEMJRHEZKmZ0yWYYoraSWYQm1aUJwJF3NaA7p4tVYM3NidFc6f+0O7l9cjVfXMKR0jHPX7DnMpU++k1QfqCMQ/7ktchXnjxfec3OfbK5RdHyy1UpKF0r6rPmvP5ZSzox7w4eAmYlXKdobVny7uu4gN86raDUBvlmTRsY0eM1ZuhmfRyNoSGZfNtLRMDUGmwflxCXOrywvZtGG3UlHfLYmuog0+CVbizQl1XWH6NnVG80n1Ow5zPSFVQQN2eI4fzb5ilzlOBTHB25P7d9yeOySXC5EkV8iEhr9eGRqaXR2gSbyF4bxewSjB0Wqc+zJz4aAQTBsMmfJZsdwSkSQLzFx/krlbu7/9qiU0hWtpbwREepL7qAChuTGeRVR3aR7X/0nlz61OuEU1BJNo/hxr/EhKqeQlRoRq3BLunLVHwE/BobF5RS6A2vyuTBFfrDvHDftPsg9r27K23tZMexMkp+RnocSHntza8zjPl1n9MCefHDPBdw6fz3vfbI/4f3awWEiSiBsRlVd7aWldpzi/NnMVYgPUTlJZKiwkSIT0p0Y/gJcBrze/F/rz1gp5TV5XpsiTxQV+inu3bXFTkHD+cTh0eCRqaVZzy2OCPKJpK//2aUj6Vvgtmm/feLTRUIvQzYKrU4CfvPe26lkuBUtIqVjkFIelFJ+KqX8fnOiuYmIrkFhsuE9io7B/7eh5UJ1JrEiF14d5n6/jHU/vyBmh+qkGjpr0khq9zc5Gixr5kT8nOPVNfuihvNw0OSacUP4+km98bb4k7QuPo/GstvOifmO3Cq0xuM0NzoeJcOtyBS36qqXAY8DA4G9wFDgIyC5JrCiXbN+R2IopqWYBrxaWUdXr875I2Pr+eNDWHOWbk4Z6ohPlgLRCXJWSGrRhoh43KSn3mnufHNGhxZ1M7eUeJWoK79eTEn/7jGvybbXwI1OlipNVWSK2+TzL4Ezga1SypOB84G1eVuVIu+MHdo75/c0gOUf7eUH89Zz0a/fTnjeCmFZ86HT7YztyVKnnbElHvfI1NKU8yie+P7XWmVmRTLiXdZLH+xi1da9MZ85214Dp9PYdWcNSThttWbCWWkydXzcBmpDUsp6IYQmhNCklCuFEL/J68oUeeX/nV7MAy5mJGTLx3sambGgkpmXfiXGKOVyZ2wZztLBvejVzcsPn99AU1yX96Vf7c9ZpxRRXXcQlwKveScQltz8wgZMWy9HS/SUnEpRbz9/eJuUpipNps6BW8dwQAhRCKwC5gsh9gKN+VuWIt8UFfr56beGJ1T/5JIFG3azYMNunryyLGocWrozTmY4Rw3siRnXrOn3aIw/pS/jH1qBJgQ5Gv2cE444yIa0pNcgXm4jF/IbmaI0mToPbh3Dt4GjRITzrgZ6Ar/I16IUrcNV44Ywd+W2hIa3k4q68ml98mSlroFHE5gyUV3ViTtfqowxDrecW8LclTX49JbvjC1W1+zDsDkcry6497KRzFmyOWZ2QXvDq2kJzXAd1YgqTabOgyvHIKW0nw7+nKe1KFoZq/pnxssbMQ2ToBlpTPv8UICfXzKCg01B/nfVJwnNXL+YMpqLRw+guu5Qcyd1asMblnDzC+sZ0b+QhRt2N+cKJDdNGMZV44ZktTO24tjWSWPmyxtjTgSagMG9u2U31DwPeAU4aQU2hcLcOK8ixkmmCr1k0+fQWihNps5DOq2kwzhHZQUgpZQ98rUwO0orKb/U7Dkc6cy1WVZL72dNzb5mnaXINLQZF53GTRNOib7u9crdTF9UhS40mkJGRiH8ZJpC6bDi2LoQNAYNigq8HGoMEbK9prvfw7hhJ7D8o70Z3bs18WqRkl97o3eq7yRf8ftcOhulydS+yJdWUvdUzys6B41BA7+uxTgGKwQwpWwQh4+GuX/JZrp4NB5/cysDenSJ/mOPOIKItobPo3FCNw+fHQq6et9swgz2OHb0scZQwuuChunoFM4a1pv3tue+VDdTBIBInE9h/07sBhvIS/w+185GaTJ1Djp2+6giJ6QKAdQ3BJizdDPBsEmwWdfOMkgQMVb2UNL+pjC/nDKS2Ys3p52nEx9mcLNzrd3fhC6S1516Ad2rMemrA3h5Q13C8xU7DqReVCshcc7PWN9JvMG+5dySnMfv85Us7sh5EkWEvIVghRBdhBDvCyGqhBDVQoj7mx8XQogHhBBbhRAfCSFuy9caFO5wqoW3EsLJ+gdq9zclfa6Lz0M3X/I9RxePllBf71YOorh3V0IOInsWg4q6sWbmRLr7nfuh3STL2wqvBg9fPgYgoQt67sptCeKCLY3fp/rdtmdUn0T+yeeJIQBMlFI2CCG8wGohxBvAV4DBwAgppSmE6JfHNShckiwEkC6hGP9cIGxwUlG3pN24/Qq9PDrta8Cx2ciZ7FyLCv3MvmxUUp2n75cXA/Cn99KPCrFPYGsPaM1G2qm6x6fr3DRhGE+/XZP13Oh4OmKyWPVJtA55OzHICA3NP3qb/0jgR8AvpJRm8+vab3bwOMNJljnVacL+nL+5rVjTBNc89z7Tyouj13h1weiB3fnNtDHcM3kUNz1fwS3zP4yeDDLZudY3BBg9qCc/v3REwnNdPYIfnncq/6j+3NXn1TWBT0/8J+BroxbpQDjSBV7g0x0N9lXjhrBm5kReuGEca2ZObLFBTPW7bY9kqyelyJy85hiEEDqwHigBnpZSrhNCnAJ8TwjxXeAL4DYp5TaHa28CbgIYMkTp9bUlqRKKU8oGMfLEHlz61GpARpPCCyoiOkaNQSN6TX1DIEHvaMbLG1ly69mudq7xu8UHvjuaLXWHWPdpPZeXDeKH550KwPZ9DbjBq2sgwD7UrptP53fXnM6BIyFue7Ey068qY7yaIGQrB7ZkPlI18+XScHekZLHqk2g98uoYpJQGUCaE6AW8IoQYDfiBo1LKciHE/wOeA85xuPYZ4BmIlKvmc52K9KRKKCaramoMGpQO7hV9LNk/7HSGEJzDTXOWbHYs7bxo5ACefefTtJ8pbBoIEXtiMGUkxFVU6Gd8SR/ueqmS9bv2M6J/IZW7D8d8xlwQiusRCRrHZD5ay2B3lGRxRwx9dVRapSpJSnlACLESuBioBf6/5qdeAf7YGmtQ5A+3/2CdXhcIGxT4dEc1VauBzZ4Ed7NbPLlvIZpIP7jnJxOHM7SoW8qd+R9/MC560sm1UwDw6yJmIpxhmqyp2RfVT7JPaOsIu/p80hI9KUVm5M0xCCH6EhHfOyCE6EpkPOhDwKvAecAnwDeB/In1KFoFt/9g7a+TpiRgSDRNMHnu6hgxOacE4/iSPglOJWgYjrvF2v1NFPg8HA6EE56z8Hu0aNd1up25k1PKGUKg2e4bNiPhtZEn9qAxGHGaL2+o5ffvbMfn0TGahfeyOU04OZeO5nA6UuirI5Oy87lFNxZiDBH5DJ1IknuBlPIXzWGl+cAQoAG4WUpZlepeqvO5Y+DWyDh1Wvs9Gu/+bCJwbO6Chb0L+84FlVHpC68ueOyK0oQkrD2XYeHRQNc019IT6e7n1aAlEkwFvoiRv+XcEp5ZtT3GiXXxaphmxGk66Tx5dYEmIpVKyT5L/O/CydlKUBU+nZy8dD63BCnlRuBrDo8fACbl630VbYfbWLVTTiIQNvnLup1MGN43oYFNmpLqukOML+mDrmmEm08OIUM6lrUmO8Gk2mlahrTAp8ckzJPd75ZzS5i7YhsBF30RugBd1/A3O6U7LxjOCQU+ygb3oneBj6ffrol5fdQZJLm31YsRCEecSfx3EO8EZk0aGZ2BYZ167lpYhWlKwpLoY7e9WIlpmnzn9MFpP5Oic5O3E0MuUSeGjk19Q4DqukPYexe+8asVCeJ7fo/gzm+dxn+/kTgnQgA3f3MYL6zdGbO77u738MIN4yju3TXrMIllSCFilP26QGgiYQcdL1Ex7sG3EgQGnfB7NJb+JFKh5TS9Dog6nYBhIqR05XDiv4PSwb0cTzc+XeDzaDQE3M2xO61/AX+/41zX769ov2R7YlCOQZFX5q/dwb2vbYpufq3wz476IwmzIAp8OkdDRkopDV3EbqSt+dHpRoUmw8mQ2u+dTNDutHuW4sbO2sNdTu9lvQcQPbFMnrs6I6lwv0fw7s/Op6jQT9WuA5GZ2DbnGemLkBklz/9w3diE8awWHSEv0RHW2Bpk6xjaiyqxohMyf+0O7nl1U4whDxmS6Ys2csnoAfg9sSGjdE4BIh2Sfo+INmTZwyTZND05NddZJGuy+8n89a6cwvQLh7P27vOjTqp2fxMeLfYz2yurSgf3oqR/d2ZNGolPF65HkV4//mRq9zdR3xBwrPwypGT2ZSMzGm36elWizhS4ly5pSzrCGts7SkRPkRfqGwLct7ja8TlNwJbPDzP19MEsXL8Tv8dD0DAwJQlqo/GYMmIILx59YjR81JKmJydDauFUclvfEGDxP911VlfuOsA72/ay6bOD+DUPYwb1TAjnxL/Ha5W7mbN0Mz6PRiBspv0+vLrguTWf8MLandHTUrL8yi8Wb8ZweWr46qCeCY/le0JbLnb5aopcblCOQZEXrN2xk2hdIGxy618/jP5c3MuL3+unZq+7abHPrfmUG84ZFv2H3pKmJ3tiGRJzDPFNdouT7KSdeNMm+91AiJXb9iW8ZtbkkTE5kXhJcV0IDIdwr08DoWkYpknAiE1Er5k5kTUzJ8YY2apdB/DpWtqhShbfPb044bF8dh7nSgNJdUfnBuUYFHmhuHfXpA1m8Y9vTzFG1AldCKrrDjFheN+cND3Za+OdqpLgmOEK57jJ7cuGY7MrnIxaN5/O5acP4oV1O9E1gZRw14XDGTesiINNIW6ZvyEmn2AZwXjNK6eTUbwch8UD3xnt+P3lq/M4l7t81R2dG1SOQZEXImNDx+C1BbY14PKvtbxO/kjI4MZ5FdHY8ZSyQS0Wl7PH+OONan1DgBmLIoYrnONajcfe3BrNhyQzaj85/1TW/fx8FvzwLN67eyKXj43s5gf27OLaCBYV+pk2NvYU8P1xg3nyyjL8Hg2/R8OrCx747miuPnOo41rzJbqXS/nvjiYM2F5RJwZF3rB24tV1BwHBqIE92N8Y5OUPW54MtJRIrV1lPvV+5q/b6ToEkw1PvbWN+749Ou3px6lRbVp5MQsqatOeluobAixYXxvz2IKKWm4/fzjv/myi69h+PjqPc73LT7VGVa3kDuUYFHmlqNDPhOH9Yn62jFlLyTZ2nIlxqG8I8PTKBPHfKH6P4LpxQ3h2Tfr5D8n403s7OHVAd64eN5TxJX145tqxWI40nZCgk4qtE46yHhIWV9VxWenAGLHDdOTaCedDA8lpjWqWg3uUY1C0Og9PLeXEHl14YkVN+henwBLgy4RMjUPt/iZ8uh5N7sbzva8P5p7LRhMwJfPe25nR2pNgZgAAHxBJREFUWuzc++omkCT0Y0ROXIf4+PNDVNcdQsQlop1UbO3U7DnM6pp9+D0aQSO2Iupo2OS+xZv55dLNPD6tLKPej1zvuvOtgaSqlTJDNbgp2oz563Yw65VNWUvTeXWB3lw95MaopGowy+QaO/brKz6p53vPriXF5NHUnydOf8mjgZRJlTHSrn/GoqqEk1l8g6CFvUkuFR111+3U+GfvGO+stDutJIUiHVePG8rg3l359z9+kFYi24mQIQkZkp8urEorKgfZlTIWFfqZ/NUTWbTBOS8ipIxe7/XodPOmVnVNhd5sbC1SpTW6egRSHCuprW8I8I/qz9m+r5GLRvZnw84DjuE6U0akvuMlN3SRPizXkXfdqlopM5RjULQpowb2xOfRMpKAiCedqJxFtsZhx5dHkj53NCyj1zvdXxDp1k6HLsCU7r+Db57Wjwe++9VoQvo/X6yMvs+z73yS9DoJjn0RR8MGH9UdzDhP0VF6BNQsh8xQ5aqKNiW+vDDDlIEjyUodsy1l/PaYE5M+ZzexRYX+qJxFgU+ni1fjiSvLWP9fFzD3+1+LKd21own49ffK+MnE4a4+H8ApfbtFTwrTF1a5cj4WTo3epoSfvbKJMx58K6mEhJPjCxoGB5uC1DcEqG8IULXrQLT81v5z/HNtQS7Kmo8X1IlB0ebEJx7vX7yJ16vcyU44keoUkE2S85pvnMx/v7GFRodTTTevHt0x2+UsgkZEn8gyPpNLB2JKeUxFNRzmsjEDOW9EP846JXK6qdlzOEFYMBnf/dpg6hsCrNyyNyOnAKTM6RhmRMvK6cQVv+tuCoUxJfzohQ0cDRlomsCnazSFDLp6BE1hSVdv5LuQUtLV63ElgZ5PklVUtWYZa0comVXJZ0W75Po/rmPFx4kSEqkQgL/5FJDr3WB9Q4DyXy5PMMJW0haSDxhyW0dftesA33vmvZh7+D0apcU9ef/T/dHHppUXU9y7G0+v3IanuSrJDZqIdDunk/T2ezQW/PCsqIy3k5x5dd0hbpxXkVV/R7pBQ61tOFszoW69ly4EIcNk9mWjkjYU5gKVfFZ0Km6/4DTe2bYvoylpErjzguF5+UddVOjniSvL+OnCqmhOw6PBI1NLo1pE8fF3XRMx8fe3Nn/OPzbv4cKR/R0rYZxOOULAb68Zy/7GIJW7DvBlY5DH3twaNcgBnJ3CiT18fHkkhIYgZJrceM4wLj+9mMlzV6cuc7KtJZnBLCr007OrF48myCYwlCon1NpVT62ZUHfSwrrn1U00BsLc9M1TcvpeLUU5BkW7pLh3V4Rwm7o9xqNvbmXiiH5pG76cSLdTderktl7nFH9vDEQG85QO7sWFv36brXsiIoEvVdQ6DsNJlSAtKvTTu8DH+IcSBxw5sa8hyBu3T0j4HuLv//WhvXmnpj56na4JHpkaGR6UymAW9+5KKNu63DjsOaHWrnpqzYR67f4mTIfyuwff2EKB35PXk0OmKMegaJcUFfqZfdko7nl1U2YXSsklT66ii8cTs+NMZ/Td7lTjO7nt9501eST3vBK73jlLN1Pg06JOweLjPY28tfnzhGE4U8oGMfLEHlTuOkBZs3aTRXXdITTcDVUImfDKh7Vcf/YwIBKmKu7d1VEw8PbzDTbVHaJPoZ+zTilKegKyG8yiQj93XXQaDy5LnLaXjAKfTtiUGKYZU4pr5YTaouqpNctYC3w6wSSntdmvb+Li0QPaTc5BOQZFu+XqM4dSVetcj58M6x9eyIiEKaYvquKjzw7x3JpPUsa0s9mpxjuTW84tiRpbC6+msSTJ/IZ/bN6T4BiSOajXKnczY9HGjGL6T7+9naff3o5HIybxO6VsEKtr9iW8z+TSgdFri3t3JWg4G0zLGY4Y0D2hKS8Zfl1j+kWncVnpQNbU7EtaNtravQatWcbaGDTwaMJxHKwuRLsq+1WOQdFuqW8IJJ0k5pZAWPLb/9ve/HfnPodsdqpOzmTuyhriQ1+BsMG5p/ZhuW02g8WFI/unveeMlzcy8sQezHw5M6dgJ2wSbbq7q7kZcMaiKgJhmdQRrq7Zh2Ez0l490kxndyhBw0C67NQIGCb//cYWTijwJa0Ma6teg3zLcVgU9+6KnsQxSGReHWCmKMegaLc4Cr/lgHijn004wWltPl3jpgnDePrtGqQpCRgSTRP88o0tnNjDx2eHjs1eOK1/QcJpIZmDqnQI62RL0JDc/mJlQv7Z/p1YDsruh8KGpHr3Qf747g6CxjHH5dQIpQNnn1rE6pr6mPdxUsSNp7WMdDz5VOe1v8cjU8dwx4IqDJtzEMCjV5S1m9MCKMegaMekGrvZEo6GwjFGP5udajJnctW4IVwyegCXPrUakNEKlP2E+c20Mby3/UsuHNk/wSnUNwQ42BTkSDBWTuNIMEwXr54ggNcSnMLcdkfolMuQwP86dFSbQHEvP7sPBKLnBk0XXD52MD84Zxg3v7CBI3GhNSvRnMz4t4aRzhduCxje+1c9O+obGFpUGM3rtCeUY1C0W+wGWwOOtEA2w44pBWtq9kV3pqGwwZeNAW6eMIx9DUGGFnWjVzcv9Q2BmNp9+z94+9p0IQiGDa4sH0x13UEONYXxCEHQ9p5eTePkvt35zumDE9Zj5RU8mkgw2oaEO176MKOy3WyYNWlktFw001xG7YHYotWQEWnkW3Lr2QTDsQ6tKRRm0+6DfO+Z9zqcEF86MilgsOdz2iOqwU3R7rGM8g1/WscXjckF6q49czDPr93l6p5uC2G/NrgnE07ty/++s93xH/x/vfJPXliXXm7b3uxmdzIA3/jVWwRyPRouAwr8On+54UwKfDoXP/GOYww8U7r7PTx99en84M8fxMz9tprb7J83vhEw03kZ7aGLOBvl3tZANbgpOi3WDv2DWRdx0s+WOr6mwKczdewQPt13JKYuPxluTd+Huw7y4a6DAAmJ2st/u4ZPXcyr1kWk8a667hB/WrOdFR/vw68BmsbYIb3b1CkABEKRfovZr29KqeiaCZGKJolP1wjZwmBeXWv+8hPDS5k2uLUnCfCWltq2FwdnoRyDokPx6a8mccX/vMMHOw/FPG7ISFXH8zecScUn9dw47wP2N+UuLm/naMjkjpc+dOUUImuLNDHZCZiAafLu9vROrDW497VNbhqiXXP9+JPY9WVTglxHJOka+0b2Mli3ZcPtTQK8Jf0Q7cnBWSh1VUWHY+GPz+HJK8uSqqSWn1zEh7Mv5jfTxqALdw1hmbJqW/sw6LnAq2k5dQoAJxT4uH/J5oTHf3rhcO6dPCpGgdb63Vm77vi1OSnlZvLa1iBb5V67gzscCHM0FKncaksVWlAnBkUHxU1Z43dOH4ymadFqo6BhEgybGauRdlR8usZV44qZv24XgkipqtMEt3xUfv3qb1scJ9k9uGwLuqBZgdbkvimjGF/Sh6pdByjw6a533fnoWG5pOCebUtv2OuNCOQZFh8VNWWP8P9a/VX+eIFvRWZlwahHXjDuJiSMGAJKPPovIenuI9BT4dYHQBP/xjZOiTYC5IpWMkiGhqTlJO+vVTfxicXW0K31aeTELKmpjwipA1HE0Bo3of6eUDozpih9fUkR13UFGDezpWtHWIlfhnExLbVM5uLbMO6iqJMVxx/y1OzLXYOqEaAJum1hCfUOQ511UVrUGXbwaS249O+oAFm2o5Q+rP0FKSdg8Vk3m00VS3SGvLnjsitKolEg6g9/WFUWvV+5O6KGRkBNHpaqSFAqXXH3mUC4ePYDn3/uUD3cd4Fsj+vHuJ/Us++eemNdNOLUP08oH88J7n7L20/3RhJyuC8KG7PAhKVPCb96qaetlxOBtni/xaX1jzLhSC+vnZE4BIn0Udy2sikqJpEtQt3U4J/5UC8dme7RVYl05BsVxSVGhn//81mnRn6/5xsnU7DnM36s/ByQXjToxqmw6uXRgQu/BP6o/5+7jJCTVmgTCBqGwwe0vVrboPkFD8tyaT1wZ/NZUWE2GPQSVTtm2NcibYxBCdAFWAf7m91kkpZxte/5J4HopZWG+1qBQZEJJ/+4xMtd24mPH3x83lJc+2EVl7cHWWl6nxKsLBJEQUWSynGDq/67Nyb0Xrd+NEM6lsXbaSrwvGe3BUeWzXDUATJRSlgJlwMVCiDMBhBDlQO88vrdCkXf+8O9fx5OfatjjBiEEv7369GilVLzUd0vw6IJbzzvVVQnplLJBrJk5kRduGMeamRNbvY+gviFA1a4DURmWbEpfc0mrJJ+FEN2A1cCPgApgOXAVsM3NiUElnxXtldcrd3NbC8MexzN+XWA0J5YzxasLdE3EJI1j7u3RePdnE4Hkgn2tjVOlUbIEeS6qktpl8lkIoQPrgRLgaSnlOiHE7cDrUsrPRIrmIyHETcBNAEOGDMnnMhWKrLESh0+t2Maf3t0R89zFo/oxoGcX/rJuFx5d42jIIAcyRJ2KQIaddQK4+ZvDuOGcyGQ6axLdC+t28Od3d0ST0149MqLUPushGa1VFurkAMaX9EmZIG8rR9ZaJ4ZewCvAbOBB4FwpZVgI0aBODIrOQn1DgOq6Q4CMqaW3DE+BT+eSJ9+JEZVTuMejwYyLRjBuWJHjjttSub3hnIjjcGNUcylHkcrBJCuJfebasdwy/8PoICWICBC+cMM4Sgf3ymoddtrlicFCSnlACLESOI/I6aGm+bTQTQhRI6UsaY11KBT5JDIPuq/j45aheOyKUqYv2ogmIGxKpl94GiNO7A4Idu0/wn2vVyvHkYSwGdGc6uLRCJsmN04YxuVfK47uuC3++O6n0RNFKnKpt5TOwSQriQXR5olmJ/JZldQXCDU7ha7At4CHpJQDbK9pUE5BcTyRTjbh4lEDqK47CAieWP4x63eqqqd4jjYnJH779nZ+9/Z2/F5nzaR0xj1X/QtuHEyySqNRA3u0q4ooi3yeGE4E/tycZ9CABVLKJXl8P4WiQ5Aqdhw5dfQDYMLwvpz/2Er+9cWR1lxeh0JCQvLZ7Y47V2WhbhxMspJYgKFFBdFu7/aQIIc8OgYp5Ubga2leo3oYFIoUfLt0II8vb1/dye2VAr+OYUrXO+5c9S+4dTDWabG67hAbdnzJb5Zv5bYXK+miA1qkJDUXeYVcoLSSFIp2TH1DgLG/XN7Wy+gQCOCX3xnN1WcOzei6XFQlOekdOSWxX6vcnbSrOx/6TO06+az4/9u79/CoyjuB49/fXDIJCVINgqvxCkQFqlix4loRRahUpV5x1S6rXW1r9bHesUW3VbRPXWu3uuxji1af1vrQIiyIYN0tKxVFULkETNBVoLgmCEqKQEKYZGbe/eOcSebM/XIyMyG/z/PkIXNm5sz7MvD+znkvv1ep/NTWBHjyH8boWoksGOChJU0cfVhVQobVdHKZFpoqiGSTcru1Lchdf0zzPUYiJU+3HaWBQakyF210bp+7nje2HDwbBMXyeyDFOrWcBEOG7/1+HRFjXF0oBplnHmUKMM27O9ImXgyGKflspCgNDEqVuWjD9strTuPVxh3cv6gxoYH50ZST6ApHeGXjdpp2tJWknIVwIyhE7be3E713wUb2HQgxa+mmgtcpFDq1tbUtyKuNn6bdKe/CUUPK4m4BNDAoVdaSXaWuuf8CmrbvZW9HJ4dU+R3dJrecP4LWtiDPvLHV9c13SqnS5+Gq0+t4d1srB7oibPtb5i08w2HDgy830Rk2Ba9TKGRq60sNLdw7fwPBUPrx3GvOzG1spDfpns9KlalU+wHvbu+kZfd+NjTvYYDfm9Aw1dYEmDHlZNbefwE/u2w0Rwwsj6vQbA2o8OL3OtPlGAyTRg3lhZvOYsH3z6bCmzl7YVfEJOzb4BHht29tY/POfTmVKd+prdHvMFNQ8HuFUUcOyqlMvUlnJSlVpjZ88gXfeuZtR7qESr8nYd7+OcNref7GcWnP9cLqj/nJy434xENHDhnrqnxCR4ZGzW2Vfg8PXDSyuwuoo8uqf4XXS9hEeOzKUwG4c15Dd/I9j5BzHqrpZx3DQ9/8ctavz3bmUaxk32GsKr+HiIHHrsw/FUc6+c5K0sCgVJlKll8nlfnfHcfY42szni86CHvREyvYsa8z43m9HiHsQuY/vwc8HuHro45g8YZPEz9HYECFLyG7aNP2vdzw3DuOvnmfB97+0QUAdpdaF7f/cX1eGVqX3TG+ew+ObAapcx3ITvUdBnwe/uXikYw+alCvLmrT6apKHWTiF2AFwxFC4UjSK+MVH+3KGBhiZ82snjmJOSu28NNXPkj7niq/h7ZgOO86RHVFIOARRgwZSE3gM8c5qwNenrruKwyqqnA0ktE/4wdsQxErIIyvP5zx9Yez4ZMvCPi8hDpzL+ebmz+nvTNMY8seZi3dhM9j7SX940tGcl2SPv9cM57Gf4ed4TC3njeCa888pmwGmpPRwKBUGYudH19d4WXKEyuSBobxIwbnfO7vjB/GFV+p45k3tvKr17cmzHR65NLRzFq6Kb+CJxEMRZi9/COspWg9QuFIynUHq7bsSnG2ntLWHVpFOM+ej5++8j4VPm9C8Ju5sBEMOS+WSyabNQ7lRgODUmXOkZ11WuJit3OG12a8W0h37hlTTubGc06gafse9naEOKTK191QN/zfbl5c11JwHaK84mHaGXU8v+rj7juBUMSwYG1zQjrt1rYgz67clnAOnwfHQG1tTYAHLhrJzEW57cEtQGcYOsPJ7zQefLmJC0cf4UpDXsq9FfKhgUGpPiR69fnfTTvYuqudr48cmndQiBWbvC/W5l3uronY3xVO2NAobKfT9gqIwINTrbQWzbs7qPB6CMYNHlw9NnHjrtFHDaImkHjlL1jjJKG42yyvgM8jaTcK8nklp5XIxdrwpxg0MCjVx9TWBIo25/2MYw9jfZFSf4cNYLCu/MVKQR4/RRRgUUMLC9Y3O2YF1R1aldD4+73wp9vGs+nTvdwzf6MjwISNtc4hnWAoQnWFN6uyu7nhTznQdQxKqZS+e+6wknzuT16yuoX+9YpTqPR7qA70NNDtneHuNR2tbUGgZ5C30u9hYMBHpd/D41eNYfjQgUwdcxRPTx/LAH92jXyUIFw8+00WN6TvSku13iRatr5I7xiUUinV1gS4a1I9j//5w6J+rmB140S7zpZ/8Bk/XtxEe8zMo/iVx8kGeaPdO0cOqiSSNlNRolDEEIqYjKul3drwp5zoHYNSKq1rzzyGzOuM3dUZMTRut7qwamsCnHfSkISZR8lWHtfWBDj16C9RWxPgpYYWzn70Nb71zNtcPPtNpo2t676j8OVQoWgjn4pbG/6UEw0MSqm0amsC/GBi8XfgnbVkk6OraNrpdY7np42tS7sQLb57Z96aZn7/7a9y1+R67pg0Iuty7AuG2NPRmbJrKFk3VroNf1rbgmz45Ata24KO38uJdiUppTK6fdKJPL1iC+1dxcuUENsd09oWZN7aZsfz89Y084OJ9Ukb4GTdOwBXP72acB4rpKc/+253g59sUDnbtQrRQWqvCAe6wohAld9XdgPWeseglMpo8859RQ0K0NMd09oWZPkHn+EVZ/9Psi6e6BV4dYU3oXvnQFckr6AQ+/50g8qx3VjJxN7FtHeGCRtrFXc5DljrHYNSKqOGT74o2mdVV3gJRSLcMmE4rzbu6E5V0R6X8iK+Hz9+yujUU/+OReu34/d66IoYTCRS8L4PhQwqN+/uIJIm71Q5DVjrHYNSKqMxRdqk3gOcW384IPzq9S3MXNTIga6IM7dShZeAT7hlQs+4R/IxhZbuoHD3pHpr9VyBChlUrq7wJqQBd+vcbtPAoJTKaPjQgZx2dO/vFxABXmncQTAUSbhDACvh3jfHHAkIc1Zs5exHX2NxQ0v3mEK89s4wnaEIv1j2IfdMPrGgsgV8knZQOZP2zjABX/Imt9Bzu00Dg1IqK9F9ENzk9whVKRrLZELhCAvWtRAMOReTJRtTcH6OhzNPqOWRy0ZT4RWy2OfH4eZzT+Ct+yYWNDhcd2hV0psWN87tNg0MSqmsDB86kOlnJeYpKsSN44/HZNFIVwe8VPo93HreCCq8zmbL7/HQ3hnuWSWdJI1FtJvmujOPZdUPJ/LcDV9NefXuOLdXeOSy0cyYcnLBV/Ox01qrA14qfB7Xzu023ahHKZWTzTv3ccNzb/PJF4XNoAn4PLx13/ms3LzLsTPatLF1zFvT3P34gYt6NrQBEja+qfR7WDnjfMdK58bte5i1ZFPa3EWxO7Il22Htrkn1vbJvQjGT7ekObkqpomptC3L6w8uyem2FV7h78on8YtmHSRvr+MYyXeOZ7Rabue7I9ruVW1nYsJ1xx9cy4xvldxWfDw0MSqmiW9zQkrA/RLyAT3jsylO7t+t042r5YEpx3Zt0a0+lVNFFV/xe/+xq3tvu3LvB74HbJjq7Y9zasKavbXzT12hgUEoVpLYmwMu3ndv9WK/m+z4NDEopV+nVfN+n01WVUko5aGBQSinloIFBKaWUgwYGpZRSDhoYlFJKOfSJBW4i8jnwcRE+ajCwqwifUy76W32h/9W5v9UXtM6xjjXGHJ7ryfpEYCgWEVmTzyrBvqq/1Rf6X537W31B6+wG7UpSSinloIFBKaWUgwYGpzmlLkCR9bf6Qv+rc3+rL2idC6ZjDEoppRz0jkEppZSDBgallFIO/TIwiMhVItIkIhERGRtzfJKIrBWR9+w/z0/y3sUi0ljcEhcu1zqLyAARWSoiH9jv+1npSp+7fL5jETndPr5ZRJ4USbZ1e/lKU+daEVkuIm0iMjvuPdfYdd4oIq+KyODilzw/eda3QkTmiMiH9r/tK4pf8vzlU+eY12TddvXLwAA0ApcDK+KO7wIuMcZ8Gfgn4PnYJ0XkcqCNvimfOv/cGHMScBpwtohMKUpJ3ZFPfZ8CbgJG2D8XFqGcbkpV5wPAA8DdsQdFxAc8AZxnjDkF2AjcWoRyuiWn+tpmAp8ZY+qBkcDrvVpC9+VT55zbrn65H4Mx5n2A+AtCY8z6mIdNQJWIBIwxQRGpAe4EvgPMK1ZZ3ZJHnfcDy+3XdIrIOqCuSMUtWK71BQ4DDjHGrLbf9zvgUuBPRSmwC9LUuR14U0SGx71F7J9qEWkFDgE2F6GorsijvgDfBk6yXxehj62QzqfO+bRd/fWOIRtXAOuMMUH78SzgcWB/6YrU6+LrDICIfAm4BPifkpSq98TW9yigOea5ZvvYQcsY0wXcDLwHbMe6gv5NSQvVi+x/xwCzRGSdiLwoIkNLWqjiyLntOmjvGERkGXBEkqdmGmNeyvDeUcCjwGT78RhgmDHmDhE5zuWiusbNOscc9wFzgSeNMVvdKqsbeqO+5a6QOic5lx8rMJwGbAX+Hfgh8HCh5XSLm/XFau/qgLeMMXeKyJ3Az4F/LLCYrnL5O86r7TpoA4Mx5oJ83icidcBCYLoxZot9+CxgrIhsw/o7GyIifzHGTHCjrG5xuc5Rc4CPjDG/LLR8bnO5vi04u8rq7GNlJd86pzDGPucWABGZB9zn4vkL5nJ9W7Gumv/Tfvwi8M8unt8VLtc5r7ZLu5Ji2LeaS4H7jDEro8eNMU8ZY440xhwHfA34sNyCQr5S1dl+7mFgEHB7KcrWG9J8x58Ce0VknD0baTqQ6xVpX9MCjBSRaPbNScD7JSxPrzLWat6XgQn2oYnAppIVqAjybruMMf3uB7gMqw85COwE/ss+fj/QDjTE/AyJe+9xQGOp69Dbdca6YjZYDUX0+I2lrkdvfsfAWKxZH1uA2diZAfrKT6o6289tA/6GNTOlGRhpH/+e/R1vxGo0a0tdj16u77FYM3o2Yo2ZHVPqevR2nWOez7rt0pQYSimlHLQrSSmllIMGBqWUUg4aGJRSSjloYFBKKeWggUEppZSDBgbVL4iI68kPRWSqiNxn/36piIzM4xx/ic2SqVQ50MCgVJ6MMYuNMdF05Jdi5RpSqs/TwKD6FbE8JiKN9j4EV9vHJ9hX7/PtPP0vRPdjEJFv2MfW2vs0LLGPXy8is0Xk74GpwGMi0iAiw2LvBERksJ2SABGpEpE/iMj7IrIQqIop22QRWRWT4K2muH87SlkO2lxJSqVwOVaOoFOBwcC7IhLNbX8aMAor0+hKrD0o1gC/BsYbY/4qInPjT2iMeUtEFgNLjDHzITEtcoybgf3GmJNF5BRgnf36wVirsi8wxrSLyAysVMkPuVFppXKhgUH1N18D5hpjwsBOEXkdOAPYC7xjjGkGEJEGrBQCbcBWY8xf7ffPxcprn6/xwJMAxpiNIrLRPj4OqytqpR1UKoBVBXyOUnnTwKBUj9h9KMIU9v8jRE9XbWUWrxfgz8aYawr4TKVcoWMMqr95A7haRLx2VtHxwDtpXv+/wAkxueyvTvG6fcDAmMfbgNPt36+MOb4CuBZAREYDp9jHV2N1XQ23n6sWkfos6qOU6zQwqP5mIVZmzQ3Aa8C9xpgdqV5sjOkAvg+8KiJrsQLAniQv/QNwj4isF5FhWBvA3Cwi67HGMqKeAmpE5H2s8YO19ud8DlwPzLW7l1Zhb0GpVLFpdlWlMhCRGmNMmz1L6T+wNi76t1KXS6neoncMSmV2kz0Y3YS1cdGvS1wepXqV3jEopZRy0DsGpZRSDhoYlFJKOWhgUEop5aCBQSmllIMGBqWUUg7/D7Tmc45iSe/JAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.plot(kind = 'scatter', x = 'longitude',y ='latitude')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f47b87fd190>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.plot(kind = 'scatter', x = 'longitude',y ='latitude', alpha = '0.1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f47b88de370>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.plot(kind = 'scatter', x = 'longitude',y ='latitude', alpha = '0.4',\n",
    "            s = housing['population']/100,label = 'population', figsize= (10,7),\n",
    "#             c = \"median_house_value\",cmap = plt.get_cmap('jet'), colorbar = True\n",
    "            )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'logitude')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.image as mpimg\n",
    "california_img = mpimg.imread('./california.png')\n",
    "housing.plot(kind = 'scatter', x = 'longitude',y ='latitude', alpha = '0.4',\n",
    "            s = housing['population']/100,label = 'population', figsize= (10,7),\n",
    "#             c = \"housing_median_age\",cmap = plt.get_cmap('jet'), colorbar = True\n",
    "            )\n",
    "plt.imshow(california_img,extent=[-124.55, -113.80, 32.45,42.05], alpha = 0.5)\n",
    "plt.ylabel('Latitude')\n",
    "plt.xlabel('logitude')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Corelation between data labels;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "median_house_value    1.000000\n",
       "median_income         0.688075\n",
       "total_rooms           0.134153\n",
       "housing_median_age    0.105623\n",
       "households            0.065843\n",
       "total_bedrooms        0.049686\n",
       "population           -0.024650\n",
       "longitude            -0.045967\n",
       "latitude             -0.144160\n",
       "Name: median_house_value, dtype: float64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.corr()['median_house_value'].sort_values(ascending = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f47b89c8460>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f47b8a3fe20>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f47b8aa34c0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f47b8840d00>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f47b88b3580>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f47b894fdc0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f47b891ecd0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f47b8c535b0>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f47b8d14700>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f47b8c99f40>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f47b8cde7c0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f47b8b8e970>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f47b875da90>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f47b8d5aaf0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f47b88d4520>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f47b79d5a00>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pandas.plotting import scatter_matrix\n",
    "attribute = ['median_house_value', 'median_income','total_rooms','housing_median_age']\n",
    "scatter_matrix(housing[attribute],figsize= (12, 8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 16, 0, 550000]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.plot(kind = 'scatter',  x = 'median_income',y = 'median_house_value', alpha = 0.1)\n",
    "plt.axis([0,16,0 , 550000])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# incorrect data on 450k, 350k and 280k \n",
    "# we can delete some of the data in later procedure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Combination of different specs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "      <th>income_cat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.88</td>\n",
       "      <td>41.0</td>\n",
       "      <td>880.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>322.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>8.3252</td>\n",
       "      <td>452600.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.86</td>\n",
       "      <td>21.0</td>\n",
       "      <td>7099.0</td>\n",
       "      <td>1106.0</td>\n",
       "      <td>2401.0</td>\n",
       "      <td>1138.0</td>\n",
       "      <td>8.3014</td>\n",
       "      <td>358500.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-122.24</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1467.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>496.0</td>\n",
       "      <td>177.0</td>\n",
       "      <td>7.2574</td>\n",
       "      <td>352100.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1274.0</td>\n",
       "      <td>235.0</td>\n",
       "      <td>558.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>5.6431</td>\n",
       "      <td>341300.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1627.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>259.0</td>\n",
       "      <td>3.8462</td>\n",
       "      <td>342200.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "0    -122.23     37.88                41.0        880.0           129.0   \n",
       "1    -122.22     37.86                21.0       7099.0          1106.0   \n",
       "2    -122.24     37.85                52.0       1467.0           190.0   \n",
       "3    -122.25     37.85                52.0       1274.0           235.0   \n",
       "4    -122.25     37.85                52.0       1627.0           280.0   \n",
       "\n",
       "   population  households  median_income  median_house_value ocean_proximity  \\\n",
       "0       322.0       126.0         8.3252            452600.0        NEAR BAY   \n",
       "1      2401.0      1138.0         8.3014            358500.0        NEAR BAY   \n",
       "2       496.0       177.0         7.2574            352100.0        NEAR BAY   \n",
       "3       558.0       219.0         5.6431            341300.0        NEAR BAY   \n",
       "4       565.0       259.0         3.8462            342200.0        NEAR BAY   \n",
       "\n",
       "  income_cat  \n",
       "0          5  \n",
       "1          5  \n",
       "2          5  \n",
       "3          4  \n",
       "4          3  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "housing['rooms_per_household'] = housing.total_rooms / housing.households\n",
    "housing['bedrooms_per_rooms'] = housing.total_bedrooms / housing.total_rooms\n",
    "housing['population_per_households'] = housing.population/ housing.households"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "median_house_value           1.000000\n",
       "median_income                0.688075\n",
       "rooms_per_household          0.151948\n",
       "total_rooms                  0.134153\n",
       "housing_median_age           0.105623\n",
       "households                   0.065843\n",
       "total_bedrooms               0.049686\n",
       "population_per_households   -0.023737\n",
       "population                  -0.024650\n",
       "longitude                   -0.045967\n",
       "latitude                    -0.144160\n",
       "bedrooms_per_rooms          -0.255880\n",
       "Name: median_house_value, dtype: float64"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.corr()['median_house_value'].sort_values(ascending = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## prepare data for machine learning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "    1. Get the data by group-slicing\n",
    "    2. Seperate the labels and target value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>ocean_proximity</th>\n",
       "      <th>income_cat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17606</th>\n",
       "      <td>-121.89</td>\n",
       "      <td>37.29</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1568.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>710.0</td>\n",
       "      <td>339.0</td>\n",
       "      <td>2.7042</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18632</th>\n",
       "      <td>-121.93</td>\n",
       "      <td>37.05</td>\n",
       "      <td>14.0</td>\n",
       "      <td>679.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>306.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>6.4214</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14650</th>\n",
       "      <td>-117.20</td>\n",
       "      <td>32.77</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1952.0</td>\n",
       "      <td>471.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>462.0</td>\n",
       "      <td>2.8621</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3230</th>\n",
       "      <td>-119.61</td>\n",
       "      <td>36.31</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1847.0</td>\n",
       "      <td>371.0</td>\n",
       "      <td>1460.0</td>\n",
       "      <td>353.0</td>\n",
       "      <td>1.8839</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3555</th>\n",
       "      <td>-118.59</td>\n",
       "      <td>34.23</td>\n",
       "      <td>17.0</td>\n",
       "      <td>6592.0</td>\n",
       "      <td>1525.0</td>\n",
       "      <td>4459.0</td>\n",
       "      <td>1463.0</td>\n",
       "      <td>3.0347</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6563</th>\n",
       "      <td>-118.13</td>\n",
       "      <td>34.20</td>\n",
       "      <td>46.0</td>\n",
       "      <td>1271.0</td>\n",
       "      <td>236.0</td>\n",
       "      <td>573.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>4.9312</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12053</th>\n",
       "      <td>-117.56</td>\n",
       "      <td>33.88</td>\n",
       "      <td>40.0</td>\n",
       "      <td>1196.0</td>\n",
       "      <td>294.0</td>\n",
       "      <td>1052.0</td>\n",
       "      <td>258.0</td>\n",
       "      <td>2.0682</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13908</th>\n",
       "      <td>-116.40</td>\n",
       "      <td>34.09</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4855.0</td>\n",
       "      <td>872.0</td>\n",
       "      <td>2098.0</td>\n",
       "      <td>765.0</td>\n",
       "      <td>3.2723</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11159</th>\n",
       "      <td>-118.01</td>\n",
       "      <td>33.82</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1960.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>1356.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>4.0625</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15775</th>\n",
       "      <td>-122.45</td>\n",
       "      <td>37.77</td>\n",
       "      <td>52.0</td>\n",
       "      <td>3095.0</td>\n",
       "      <td>682.0</td>\n",
       "      <td>1269.0</td>\n",
       "      <td>639.0</td>\n",
       "      <td>3.5750</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16512 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "17606    -121.89     37.29                38.0       1568.0           351.0   \n",
       "18632    -121.93     37.05                14.0        679.0           108.0   \n",
       "14650    -117.20     32.77                31.0       1952.0           471.0   \n",
       "3230     -119.61     36.31                25.0       1847.0           371.0   \n",
       "3555     -118.59     34.23                17.0       6592.0          1525.0   \n",
       "...          ...       ...                 ...          ...             ...   \n",
       "6563     -118.13     34.20                46.0       1271.0           236.0   \n",
       "12053    -117.56     33.88                40.0       1196.0           294.0   \n",
       "13908    -116.40     34.09                 9.0       4855.0           872.0   \n",
       "11159    -118.01     33.82                31.0       1960.0           380.0   \n",
       "15775    -122.45     37.77                52.0       3095.0           682.0   \n",
       "\n",
       "       population  households  median_income ocean_proximity income_cat  \n",
       "17606       710.0       339.0         2.7042       <1H OCEAN          2  \n",
       "18632       306.0       113.0         6.4214       <1H OCEAN          5  \n",
       "14650       936.0       462.0         2.8621      NEAR OCEAN          2  \n",
       "3230       1460.0       353.0         1.8839          INLAND          2  \n",
       "3555       4459.0      1463.0         3.0347       <1H OCEAN          3  \n",
       "...           ...         ...            ...             ...        ...  \n",
       "6563        573.0       210.0         4.9312          INLAND          4  \n",
       "12053      1052.0       258.0         2.0682          INLAND          2  \n",
       "13908      2098.0       765.0         3.2723          INLAND          3  \n",
       "11159      1356.0       356.0         4.0625       <1H OCEAN          3  \n",
       "15775      1269.0       639.0         3.5750        NEAR BAY          3  \n",
       "\n",
       "[16512 rows x 10 columns]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_mid_val = train_set.median_house_value.copy()\n",
    "train_set.drop(['median_house_value'], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 16512 entries, 17606 to 15775\n",
      "Data columns (total 11 columns):\n",
      "longitude             16512 non-null float64\n",
      "latitude              16512 non-null float64\n",
      "housing_median_age    16512 non-null float64\n",
      "total_rooms           16512 non-null float64\n",
      "total_bedrooms        16354 non-null float64\n",
      "population            16512 non-null float64\n",
      "households            16512 non-null float64\n",
      "median_income         16512 non-null float64\n",
      "median_house_value    16512 non-null float64\n",
      "ocean_proximity       16512 non-null object\n",
      "income_cat            16512 non-null category\n",
      "dtypes: category(1), float64(9), object(1)\n",
      "memory usage: 1.4+ MB\n"
     ]
    }
   ],
   "source": [
    "train_set.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "      <th>income_cat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4629</th>\n",
       "      <td>-118.30</td>\n",
       "      <td>34.07</td>\n",
       "      <td>18.0</td>\n",
       "      <td>3759.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3296.0</td>\n",
       "      <td>1462.0</td>\n",
       "      <td>2.2708</td>\n",
       "      <td>175000.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6068</th>\n",
       "      <td>-117.86</td>\n",
       "      <td>34.01</td>\n",
       "      <td>16.0</td>\n",
       "      <td>4632.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3038.0</td>\n",
       "      <td>727.0</td>\n",
       "      <td>5.1762</td>\n",
       "      <td>264400.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17923</th>\n",
       "      <td>-121.97</td>\n",
       "      <td>37.35</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1955.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>999.0</td>\n",
       "      <td>386.0</td>\n",
       "      <td>4.6328</td>\n",
       "      <td>287100.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13656</th>\n",
       "      <td>-117.30</td>\n",
       "      <td>34.05</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2155.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1039.0</td>\n",
       "      <td>391.0</td>\n",
       "      <td>1.6675</td>\n",
       "      <td>95800.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19252</th>\n",
       "      <td>-122.79</td>\n",
       "      <td>38.48</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6837.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3468.0</td>\n",
       "      <td>1405.0</td>\n",
       "      <td>3.1662</td>\n",
       "      <td>191000.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3376</th>\n",
       "      <td>-118.28</td>\n",
       "      <td>34.25</td>\n",
       "      <td>29.0</td>\n",
       "      <td>2559.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1886.0</td>\n",
       "      <td>769.0</td>\n",
       "      <td>2.6036</td>\n",
       "      <td>162100.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4691</th>\n",
       "      <td>-118.37</td>\n",
       "      <td>34.07</td>\n",
       "      <td>50.0</td>\n",
       "      <td>2519.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1117.0</td>\n",
       "      <td>516.0</td>\n",
       "      <td>4.3667</td>\n",
       "      <td>405600.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6052</th>\n",
       "      <td>-117.76</td>\n",
       "      <td>34.04</td>\n",
       "      <td>34.0</td>\n",
       "      <td>1914.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1564.0</td>\n",
       "      <td>328.0</td>\n",
       "      <td>2.8347</td>\n",
       "      <td>115800.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17198</th>\n",
       "      <td>-119.75</td>\n",
       "      <td>34.45</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2864.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1404.0</td>\n",
       "      <td>603.0</td>\n",
       "      <td>5.5073</td>\n",
       "      <td>263800.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4738</th>\n",
       "      <td>-118.38</td>\n",
       "      <td>34.05</td>\n",
       "      <td>49.0</td>\n",
       "      <td>702.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>458.0</td>\n",
       "      <td>187.0</td>\n",
       "      <td>4.8958</td>\n",
       "      <td>333600.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>158 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "4629     -118.30     34.07                18.0       3759.0             NaN   \n",
       "6068     -117.86     34.01                16.0       4632.0             NaN   \n",
       "17923    -121.97     37.35                30.0       1955.0             NaN   \n",
       "13656    -117.30     34.05                 6.0       2155.0             NaN   \n",
       "19252    -122.79     38.48                 7.0       6837.0             NaN   \n",
       "...          ...       ...                 ...          ...             ...   \n",
       "3376     -118.28     34.25                29.0       2559.0             NaN   \n",
       "4691     -118.37     34.07                50.0       2519.0             NaN   \n",
       "6052     -117.76     34.04                34.0       1914.0             NaN   \n",
       "17198    -119.75     34.45                 6.0       2864.0             NaN   \n",
       "4738     -118.38     34.05                49.0        702.0             NaN   \n",
       "\n",
       "       population  households  median_income  median_house_value  \\\n",
       "4629       3296.0      1462.0         2.2708            175000.0   \n",
       "6068       3038.0       727.0         5.1762            264400.0   \n",
       "17923       999.0       386.0         4.6328            287100.0   \n",
       "13656      1039.0       391.0         1.6675             95800.0   \n",
       "19252      3468.0      1405.0         3.1662            191000.0   \n",
       "...           ...         ...            ...                 ...   \n",
       "3376       1886.0       769.0         2.6036            162100.0   \n",
       "4691       1117.0       516.0         4.3667            405600.0   \n",
       "6052       1564.0       328.0         2.8347            115800.0   \n",
       "17198      1404.0       603.0         5.5073            263800.0   \n",
       "4738        458.0       187.0         4.8958            333600.0   \n",
       "\n",
       "      ocean_proximity income_cat  \n",
       "4629        <1H OCEAN          2  \n",
       "6068        <1H OCEAN          4  \n",
       "17923       <1H OCEAN          4  \n",
       "13656          INLAND          2  \n",
       "19252       <1H OCEAN          3  \n",
       "...               ...        ...  \n",
       "3376        <1H OCEAN          2  \n",
       "4691        <1H OCEAN          3  \n",
       "6052           INLAND          2  \n",
       "17198      NEAR OCEAN          4  \n",
       "4738        <1H OCEAN          4  \n",
       "\n",
       "[158 rows x 11 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rows = train_set[train_set.isnull().any(axis = 1)]\n",
    "rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "# rows.dropna(subset=['total_bedrooms'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "# use midian to replace the missing value \n",
    "\n",
    "from sklearn.impute import SimpleImputer\n",
    "imputer = SimpleImputer(strategy = 'median')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SimpleImputer(add_indicator=False, copy=True, fill_value=None,\n",
       "              missing_values=nan, strategy='median', verbose=0)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_set= train_set.drop('ocean_proximity', axis = 1)\n",
    "imputer.fit(train_set)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-1.1851e+02,  3.4260e+01,  2.9000e+01,  2.1195e+03,  4.3300e+02,\n",
       "        1.1640e+03,  4.0800e+02,  3.5409e+00,  1.7950e+05,  3.0000e+00])"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imputer.statistics_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = imputer.transform(train_set)\n",
    "train_final = pd.DataFrame(X, columns= train_set.columns, index=train_set.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>income_cat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17606</th>\n",
       "      <td>-121.89</td>\n",
       "      <td>37.29</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1568.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>710.0</td>\n",
       "      <td>339.0</td>\n",
       "      <td>2.7042</td>\n",
       "      <td>286600.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18632</th>\n",
       "      <td>-121.93</td>\n",
       "      <td>37.05</td>\n",
       "      <td>14.0</td>\n",
       "      <td>679.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>306.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>6.4214</td>\n",
       "      <td>340600.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14650</th>\n",
       "      <td>-117.20</td>\n",
       "      <td>32.77</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1952.0</td>\n",
       "      <td>471.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>462.0</td>\n",
       "      <td>2.8621</td>\n",
       "      <td>196900.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3230</th>\n",
       "      <td>-119.61</td>\n",
       "      <td>36.31</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1847.0</td>\n",
       "      <td>371.0</td>\n",
       "      <td>1460.0</td>\n",
       "      <td>353.0</td>\n",
       "      <td>1.8839</td>\n",
       "      <td>46300.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3555</th>\n",
       "      <td>-118.59</td>\n",
       "      <td>34.23</td>\n",
       "      <td>17.0</td>\n",
       "      <td>6592.0</td>\n",
       "      <td>1525.0</td>\n",
       "      <td>4459.0</td>\n",
       "      <td>1463.0</td>\n",
       "      <td>3.0347</td>\n",
       "      <td>254500.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "17606    -121.89     37.29                38.0       1568.0           351.0   \n",
       "18632    -121.93     37.05                14.0        679.0           108.0   \n",
       "14650    -117.20     32.77                31.0       1952.0           471.0   \n",
       "3230     -119.61     36.31                25.0       1847.0           371.0   \n",
       "3555     -118.59     34.23                17.0       6592.0          1525.0   \n",
       "\n",
       "       population  households  median_income  median_house_value  income_cat  \n",
       "17606       710.0       339.0         2.7042            286600.0         2.0  \n",
       "18632       306.0       113.0         6.4214            340600.0         5.0  \n",
       "14650       936.0       462.0         2.8621            196900.0         2.0  \n",
       "3230       1460.0       353.0         1.8839             46300.0         2.0  \n",
       "3555       4459.0      1463.0         3.0347            254500.0         3.0  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_final.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 16512 entries, 17606 to 15775\n",
      "Data columns (total 10 columns):\n",
      "longitude             16512 non-null float64\n",
      "latitude              16512 non-null float64\n",
      "housing_median_age    16512 non-null float64\n",
      "total_rooms           16512 non-null float64\n",
      "total_bedrooms        16512 non-null float64\n",
      "population            16512 non-null float64\n",
      "households            16512 non-null float64\n",
      "median_income         16512 non-null float64\n",
      "median_house_value    16512 non-null float64\n",
      "income_cat            16512 non-null float64\n",
      "dtypes: float64(10)\n",
      "memory usage: 1.4 MB\n"
     ]
    }
   ],
   "source": [
    "train_final.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ocean_proximity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  ocean_proximity\n",
       "0        NEAR BAY\n",
       "1        NEAR BAY\n",
       "2        NEAR BAY\n",
       "3        NEAR BAY\n",
       "4        NEAR BAY"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_cat = housing[['ocean_proximity']]\n",
    "housing_cat.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<1H OCEAN     9136\n",
       "INLAND        6551\n",
       "NEAR OCEAN    2658\n",
       "NEAR BAY      2290\n",
       "ISLAND           5\n",
       "Name: ocean_proximity, dtype: int64"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing['ocean_proximity'] .value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "# transform from text to numbers \n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "encoder = LabelEncoder()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/tecty/.local/lib/python3.8/site-packages/sklearn/preprocessing/_label.py:251: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
      "  y = column_or_1d(y, warn=True)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([3, 3, 3, ..., 1, 1, 1])"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_cat_encoded = encoder.fit_transform(housing_cat)\n",
    "housing_cat_encoded"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['<1H OCEAN', 'INLAND', 'ISLAND', 'NEAR BAY', 'NEAR OCEAN'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "encoder.classes_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<20640x5 sparse matrix of type '<class 'numpy.float64'>'\n",
       "\twith 20640 stored elements in Compressed Sparse Row format>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import OneHotEncoder\n",
    "encoder = OneHotEncoder()\n",
    "housing_cat_one_hot  = encoder.fit_transform(housing_cat_encoded.reshape(-1,1))\n",
    "housing_cat_one_hot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0., 0., 0., 1., 0.],\n",
       "       [0., 0., 0., 1., 0.],\n",
       "       [0., 0., 0., 1., 0.],\n",
       "       ...,\n",
       "       [0., 1., 0., 0., 0.],\n",
       "       [0., 1., 0., 0., 0.],\n",
       "       [0., 1., 0., 0., 0.]])"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_cat_one_hot.toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0., 0., 0., 1., 0.],\n",
       "       [0., 0., 0., 1., 0.],\n",
       "       [0., 0., 0., 1., 0.],\n",
       "       ...,\n",
       "       [0., 1., 0., 0., 0.],\n",
       "       [0., 1., 0., 0., 0.],\n",
       "       [0., 1., 0., 0., 0.]])"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# one step to transform to one hot array \n",
    "from sklearn.preprocessing import LabelBinarizer\n",
    "encoder = LabelBinarizer()\n",
    "hosing_cat_one_hot = encoder.fit_transform(housing_cat)\n",
    "housing_cat_one_hot.toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<20640x5 sparse matrix of type '<class 'numpy.float64'>'\n",
       "\twith 20640 stored elements in Compressed Sparse Row format>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# one step to transform to one hot array \n",
    "from sklearn.preprocessing import LabelBinarizer\n",
    "encoder = LabelBinarizer(sparse_output=True)\n",
    "hosing_cat_one_hot = encoder.fit_transform(housing_cat)\n",
    "housing_cat_one_hot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define a new encoder for rooms per household, bedrooms per rooms, population per household and ..\n",
    "from sklearn.base import BaseEstimator, TransformerMixin\n",
    "\n",
    "rooms_ix, bedrooms_ix, population_ix, household_ix = \\\n",
    "    [list(housing.columns).index(col) for col in \n",
    "     ('total_rooms', 'total_bedrooms', 'population', 'households')]\n",
    "\n",
    "class CombineAttrAdder(BaseEstimator, TransformerMixin):\n",
    "    def __init__(self):\n",
    "        pass\n",
    "    \n",
    "    def fit(self, X, y = None):\n",
    "        return self\n",
    "    def transform(self, X, y = None):\n",
    "        rooms_per_household       = X[:,rooms_ix] / X[:,household_ix]\n",
    "        bedrooms_per_rooms        = X[:,bedrooms_ix] / X[:,rooms_ix]\n",
    "        population_per_households = X[:,population_ix]/ X[:,household_ix]\n",
    "        return np.c_[X,rooms_per_household,bedrooms_per_rooms,population_per_households]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "attr_adder = CombineAttrAdder()\n",
    "housing_extra_attrs= attr_adder.transform(housing.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "      <th>income_cat</th>\n",
       "      <th>rooms_per_household</th>\n",
       "      <th>bedrooms_per_rooms</th>\n",
       "      <th>population_per_households</th>\n",
       "      <th>rooms_per_household</th>\n",
       "      <th>bedrooms_per_rooms</th>\n",
       "      <th>population_per_households</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.88</td>\n",
       "      <td>41</td>\n",
       "      <td>880</td>\n",
       "      <td>129</td>\n",
       "      <td>322</td>\n",
       "      <td>126</td>\n",
       "      <td>8.3252</td>\n",
       "      <td>452600</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>5</td>\n",
       "      <td>6.98413</td>\n",
       "      <td>0.146591</td>\n",
       "      <td>2.55556</td>\n",
       "      <td>6.98413</td>\n",
       "      <td>0.146591</td>\n",
       "      <td>2.55556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.86</td>\n",
       "      <td>21</td>\n",
       "      <td>7099</td>\n",
       "      <td>1106</td>\n",
       "      <td>2401</td>\n",
       "      <td>1138</td>\n",
       "      <td>8.3014</td>\n",
       "      <td>358500</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>5</td>\n",
       "      <td>6.23814</td>\n",
       "      <td>0.155797</td>\n",
       "      <td>2.10984</td>\n",
       "      <td>6.23814</td>\n",
       "      <td>0.155797</td>\n",
       "      <td>2.10984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-122.24</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52</td>\n",
       "      <td>1467</td>\n",
       "      <td>190</td>\n",
       "      <td>496</td>\n",
       "      <td>177</td>\n",
       "      <td>7.2574</td>\n",
       "      <td>352100</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>5</td>\n",
       "      <td>8.28814</td>\n",
       "      <td>0.129516</td>\n",
       "      <td>2.80226</td>\n",
       "      <td>8.28814</td>\n",
       "      <td>0.129516</td>\n",
       "      <td>2.80226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52</td>\n",
       "      <td>1274</td>\n",
       "      <td>235</td>\n",
       "      <td>558</td>\n",
       "      <td>219</td>\n",
       "      <td>5.6431</td>\n",
       "      <td>341300</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>4</td>\n",
       "      <td>5.81735</td>\n",
       "      <td>0.184458</td>\n",
       "      <td>2.54795</td>\n",
       "      <td>5.81735</td>\n",
       "      <td>0.184458</td>\n",
       "      <td>2.54795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52</td>\n",
       "      <td>1627</td>\n",
       "      <td>280</td>\n",
       "      <td>565</td>\n",
       "      <td>259</td>\n",
       "      <td>3.8462</td>\n",
       "      <td>342200</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>3</td>\n",
       "      <td>6.28185</td>\n",
       "      <td>0.172096</td>\n",
       "      <td>2.18147</td>\n",
       "      <td>6.28185</td>\n",
       "      <td>0.172096</td>\n",
       "      <td>2.18147</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  longitude latitude housing_median_age total_rooms total_bedrooms population  \\\n",
       "0   -122.23    37.88                 41         880            129        322   \n",
       "1   -122.22    37.86                 21        7099           1106       2401   \n",
       "2   -122.24    37.85                 52        1467            190        496   \n",
       "3   -122.25    37.85                 52        1274            235        558   \n",
       "4   -122.25    37.85                 52        1627            280        565   \n",
       "\n",
       "  households median_income median_house_value ocean_proximity income_cat  \\\n",
       "0        126        8.3252             452600        NEAR BAY          5   \n",
       "1       1138        8.3014             358500        NEAR BAY          5   \n",
       "2        177        7.2574             352100        NEAR BAY          5   \n",
       "3        219        5.6431             341300        NEAR BAY          4   \n",
       "4        259        3.8462             342200        NEAR BAY          3   \n",
       "\n",
       "  rooms_per_household bedrooms_per_rooms population_per_households  \\\n",
       "0             6.98413           0.146591                   2.55556   \n",
       "1             6.23814           0.155797                   2.10984   \n",
       "2             8.28814           0.129516                   2.80226   \n",
       "3             5.81735           0.184458                   2.54795   \n",
       "4             6.28185           0.172096                   2.18147   \n",
       "\n",
       "  rooms_per_household bedrooms_per_rooms population_per_households  \n",
       "0             6.98413           0.146591                   2.55556  \n",
       "1             6.23814           0.155797                   2.10984  \n",
       "2             8.28814           0.129516                   2.80226  \n",
       "3             5.81735           0.184458                   2.54795  \n",
       "4             6.28185           0.172096                   2.18147  "
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_transformed = pd.DataFrame(\n",
    "    housing_extra_attrs, \n",
    "    columns=list(housing.columns) +['rooms_per_household','bedrooms_per_rooms','population_per_households'])\n",
    "housing_transformed.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## feature scaling\n",
    "- normalization\n",
    "- base on max and min "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Transfrom Pipeline "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "num_pipeline = Pipeline([\n",
    "    ('imputer', SimpleImputer(strategy = 'median')),\n",
    "    ('attr_adder', CombineAttrAdder()),\n",
    "    ('std_scaler', StandardScaler())\n",
    "])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 16512 entries, 14196 to 15795\n",
      "Data columns (total 10 columns):\n",
      "longitude             16512 non-null float64\n",
      "latitude              16512 non-null float64\n",
      "housing_median_age    16512 non-null float64\n",
      "total_rooms           16512 non-null float64\n",
      "total_bedrooms        16512 non-null float64\n",
      "population            16512 non-null float64\n",
      "households            16512 non-null float64\n",
      "median_income         16512 non-null float64\n",
      "median_house_value    16512 non-null float64\n",
      "income_cat            16512 non-null float64\n",
      "dtypes: float64(10)\n",
      "memory usage: 1.4 MB\n"
     ]
    }
   ],
   "source": [
    "# naming is a side effects from tutorial, reconstruction of housing num \n",
    "housing = load_housing_data()\n",
    "housing['income_cat'] = np.ceil(housing['median_income']/1.5)\n",
    "housing['income_cat'].where(housing['income_cat'] < 5, 5.0, inplace = True)\n",
    "housing = housing.drop('ocean_proximity', axis = 1)\n",
    "\n",
    "# from sklearn.model_selection import train_test_split\n",
    "train_set, test_set = train_test_split(housing, test_size = 0.2, random_state = 42)\n",
    "train_set.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "class DataFrameSelector(BaseEstimator, TransformerMixin):\n",
    "    def __init__(self, attr_names):\n",
    "        self.attr_name = attr_names\n",
    "    def fit (self, X, y = None):\n",
    "        return self \n",
    "    def transform(self, X):\n",
    "        return X[self.attr_name].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['longitude',\n",
       " 'latitude',\n",
       " 'housing_median_age',\n",
       " 'total_rooms',\n",
       " 'total_bedrooms',\n",
       " 'population',\n",
       " 'households',\n",
       " 'median_income',\n",
       " 'median_house_value',\n",
       " 'income_cat']"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_attrs = list(train_set)\n",
    "num_attrs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_pipeline = Pipeline([\n",
    "    ('selector', DataFrameSelector(['longitude',\n",
    " 'latitude',\n",
    " 'housing_median_age',\n",
    " 'total_rooms',\n",
    " 'total_bedrooms',\n",
    " 'population',\n",
    " 'households',\n",
    " 'median_income'])),\n",
    "    ('imputer', SimpleImputer(strategy = 'median')),\n",
    "    ('attr_adder', CombineAttrAdder()),\n",
    "    ('std_scaler', StandardScaler())\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelBinarizer\n",
    "class MyLabelBinarizer(BaseEstimator, TransformerMixin):\n",
    "    def __init__(self):\n",
    "        self.encode = LabelBinarizer()\n",
    "    def fit (self, X, y = None):\n",
    "        return self.encode.fit(X) \n",
    "    def transform(self, X):\n",
    "        return self.encode.transform(X) \n",
    "cat_pipeline = Pipeline([\n",
    "    ('selector', DataFrameSelector(['ocean_proximity'])),\n",
    "    ('label_one_hop', MyLabelBinarizer()),\n",
    "])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.pipeline import FeatureUnion\n",
    "full_pipeline = FeatureUnion(transformer_list=[\n",
    "    ('num_pipeline', num_pipeline,),\n",
    "    ('cat_pipeline', cat_pipeline),\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th>0</th>\n",
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       "      <td>0.348490</td>\n",
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       "      <td>0.709162</td>\n",
       "      <td>-0.876696</td>\n",
       "      <td>1.618118</td>\n",
       "      <td>0.340293</td>\n",
       "      <td>0.593094</td>\n",
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       "      <td>-0.447603</td>\n",
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       "      <td>-1.952710</td>\n",
       "      <td>-0.342597</td>\n",
       "      <td>-0.495226</td>\n",
       "      <td>-0.449818</td>\n",
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       "      <td>1.232698</td>\n",
       "      <td>-1.382172</td>\n",
       "      <td>0.586545</td>\n",
       "      <td>-0.561490</td>\n",
       "      <td>-0.409306</td>\n",
       "      <td>-0.007434</td>\n",
       "      <td>-0.380587</td>\n",
       "      <td>-1.017864</td>\n",
       "      <td>-0.600015</td>\n",
       "      <td>0.783032</td>\n",
       "      <td>0.077507</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.108551</td>\n",
       "      <td>0.532084</td>\n",
       "      <td>1.142008</td>\n",
       "      <td>-0.119565</td>\n",
       "      <td>-0.256559</td>\n",
       "      <td>-0.485877</td>\n",
       "      <td>-0.314962</td>\n",
       "      <td>-0.171488</td>\n",
       "      <td>0.349007</td>\n",
       "      <td>-0.550364</td>\n",
       "      <td>-0.068832</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>16507</th>\n",
       "      <td>0.808883</td>\n",
       "      <td>-0.872016</td>\n",
       "      <td>0.507194</td>\n",
       "      <td>-0.603337</td>\n",
       "      <td>-0.805492</td>\n",
       "      <td>-0.675847</td>\n",
       "      <td>-0.742833</td>\n",
       "      <td>1.307215</td>\n",
       "      <td>0.290620</td>\n",
       "      <td>-1.064430</td>\n",
       "      <td>-0.005588</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>16508</th>\n",
       "      <td>1.073144</td>\n",
       "      <td>-0.759688</td>\n",
       "      <td>0.348490</td>\n",
       "      <td>0.203255</td>\n",
       "      <td>0.075188</td>\n",
       "      <td>0.287195</td>\n",
       "      <td>-0.133839</td>\n",
       "      <td>-0.436266</td>\n",
       "      <td>0.600411</td>\n",
       "      <td>-0.483382</td>\n",
       "      <td>0.069722</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>16509</th>\n",
       "      <td>0.599469</td>\n",
       "      <td>-0.755007</td>\n",
       "      <td>0.586545</td>\n",
       "      <td>-0.248786</td>\n",
       "      <td>0.072801</td>\n",
       "      <td>0.289833</td>\n",
       "      <td>0.070909</td>\n",
       "      <td>-0.496973</td>\n",
       "      <td>-0.606759</td>\n",
       "      <td>0.999514</td>\n",
       "      <td>0.020306</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16510</th>\n",
       "      <td>-1.185540</td>\n",
       "      <td>0.906510</td>\n",
       "      <td>-1.079841</td>\n",
       "      <td>0.429046</td>\n",
       "      <td>0.139628</td>\n",
       "      <td>0.308303</td>\n",
       "      <td>0.154908</td>\n",
       "      <td>0.965450</td>\n",
       "      <td>0.402175</td>\n",
       "      <td>-0.790862</td>\n",
       "      <td>0.007076</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16511</th>\n",
       "      <td>-1.414898</td>\n",
       "      <td>0.995437</td>\n",
       "      <td>1.856173</td>\n",
       "      <td>0.728414</td>\n",
       "      <td>1.853254</td>\n",
       "      <td>1.048834</td>\n",
       "      <td>1.947764</td>\n",
       "      <td>-0.685448</td>\n",
       "      <td>-0.851446</td>\n",
       "      <td>1.695203</td>\n",
       "      <td>-0.085354</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16512 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              0         1         2         3         4         5         6  \\\n",
       "0      1.272587 -1.372811  0.348490  0.222569  0.211228  0.768276  0.322906   \n",
       "1      0.709162 -0.876696  1.618118  0.340293  0.593094 -0.098901  0.672027   \n",
       "2     -0.447603 -0.460146 -1.952710 -0.342597 -0.495226 -0.449818 -0.430461   \n",
       "3      1.232698 -1.382172  0.586545 -0.561490 -0.409306 -0.007434 -0.380587   \n",
       "4     -0.108551  0.532084  1.142008 -0.119565 -0.256559 -0.485877 -0.314962   \n",
       "...         ...       ...       ...       ...       ...       ...       ...   \n",
       "16507  0.808883 -0.872016  0.507194 -0.603337 -0.805492 -0.675847 -0.742833   \n",
       "16508  1.073144 -0.759688  0.348490  0.203255  0.075188  0.287195 -0.133839   \n",
       "16509  0.599469 -0.755007  0.586545 -0.248786  0.072801  0.289833  0.070909   \n",
       "16510 -1.185540  0.906510 -1.079841  0.429046  0.139628  0.308303  0.154908   \n",
       "16511 -1.414898  0.995437  1.856173  0.728414  1.853254  1.048834  1.947764   \n",
       "\n",
       "              7         8         9        10   11   12   13   14   15  \n",
       "0     -0.326196 -0.174916 -0.211785  0.051376  0.0  0.0  0.0  0.0  1.0  \n",
       "1     -0.035843 -0.402835  0.342185 -0.117362  0.0  0.0  0.0  0.0  1.0  \n",
       "2      0.144701  0.088216 -0.661658 -0.032280  0.0  0.0  0.0  0.0  1.0  \n",
       "3     -1.017864 -0.600015  0.783032  0.077507  0.0  0.0  0.0  0.0  1.0  \n",
       "4     -0.171488  0.349007 -0.550364 -0.068832  0.0  1.0  0.0  0.0  0.0  \n",
       "...         ...       ...       ...       ...  ...  ...  ...  ...  ...  \n",
       "16507  1.307215  0.290620 -1.064430 -0.005588  1.0  0.0  0.0  0.0  0.0  \n",
       "16508 -0.436266  0.600411 -0.483382  0.069722  0.0  1.0  0.0  0.0  0.0  \n",
       "16509 -0.496973 -0.606759  0.999514  0.020306  1.0  0.0  0.0  0.0  0.0  \n",
       "16510  0.965450  0.402175 -0.790862  0.007076  1.0  0.0  0.0  0.0  0.0  \n",
       "16511 -0.685448 -0.851446  1.695203 -0.085354  0.0  0.0  0.0  1.0  0.0  \n",
       "\n",
       "[16512 rows x 16 columns]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing = load_housing_data()\n",
    "train_set, test_set = train_test_split(housing, test_size = 0.2, random_state = 42)\n",
    "housing_final = pd.DataFrame(full_pipeline.fit_transform(train_set.drop('median_house_value', axis = 1)))\n",
    "housing_label = train_set['median_house_value']\n",
    "housing_final"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# using linear regression \n",
    "from sklearn.linear_model import LinearRegression\n",
    "lin_reg = LinearRegression()\n",
    "lin_reg.fit(housing_final, housing_label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([181746.54359616, 290558.74973505, 244957.50017771, 146498.51061398,\n",
       "       163230.42393939])"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "some_data = full_pipeline.transform(train_set.iloc[:5])\n",
    "some_target = train_set['median_house_value'].iloc[:5]\n",
    "\n",
    "lin_predict = lin_reg.predict(some_data)\n",
    "lin_predict\n",
    "# print(\"Predictions:\", lin_reg.predict(some_data, some_target))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5417765553.786656"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error\n",
    "lin_mse = mean_squared_error(some_target, lin_predict)\n",
    "lin_mse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "73605.47230869901"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lin_rmse = np.sqrt(lin_mse)\n",
    "lin_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeRegressor(ccp_alpha=0.0, criterion='mse', max_depth=None,\n",
       "                      max_features=None, max_leaf_nodes=None,\n",
       "                      min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "                      min_samples_leaf=1, min_samples_split=2,\n",
       "                      min_weight_fraction_leaf=0.0, presort='deprecated',\n",
       "                      random_state=None, splitter='best')"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeRegressor\n",
    "tree_reg = DecisionTreeRegressor()\n",
    "tree_reg.fit(housing_final, housing_label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# overfitting by decision tree\n",
    "mean_squared_error(some_target, tree_reg.predict(some_data))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([64310.47895597, 69355.29716319, 68897.5471282 , 71888.25580043,\n",
       "       72955.49937348, 66009.22212093, 65706.89067586, 67986.80174613,\n",
       "       65376.99167614, 69290.01692064])"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.model_selection import cross_val_score\n",
    "np.sqrt(\n",
    "    - cross_val_score(\n",
    "        tree_reg, housing_final, housing_label, \n",
    "        scoring = 'neg_mean_squared_error',cv = 10\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([65000.67382615, 70960.56056304, 67122.63935124, 66089.63153865,\n",
       "       68402.54686442, 65266.34735288, 65218.78174481, 68525.46981754,\n",
       "       72739.87555996, 68957.34111906])"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sqrt(\n",
    "    - cross_val_score(\n",
    "        lin_reg, housing_final, housing_label, \n",
    "        scoring = 'neg_mean_squared_error',cv = 10\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',\n",
       "                      max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
       "                      max_samples=None, min_impurity_decrease=0.0,\n",
       "                      min_impurity_split=None, min_samples_leaf=1,\n",
       "                      min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
       "                      n_estimators=10, n_jobs=None, oob_score=False,\n",
       "                      random_state=42, verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "forest_reg = RandomForestRegressor(n_estimators=10, random_state=42)\n",
    "forest_reg.fit(housing_final, housing_label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([51400.48086616, 54112.6254289 , 53571.29285387, 54440.82380436,\n",
       "       54757.35653714, 48655.78236924, 50183.44202533, 53682.92168462,\n",
       "       52397.35827073, 52205.43172795])"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sqrt(\n",
    "    - cross_val_score(\n",
    "        forest_reg, housing_final, housing_label, \n",
    "        scoring = 'neg_mean_squared_error',cv = 10\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=5, error_score=nan,\n",
       "             estimator=RandomForestRegressor(bootstrap=True, ccp_alpha=0.0,\n",
       "                                             criterion='mse', max_depth=None,\n",
       "                                             max_features='auto',\n",
       "                                             max_leaf_nodes=None,\n",
       "                                             max_samples=None,\n",
       "                                             min_impurity_decrease=0.0,\n",
       "                                             min_impurity_split=None,\n",
       "                                             min_samples_leaf=1,\n",
       "                                             min_samples_split=2,\n",
       "                                             min_weight_fraction_leaf=0.0,\n",
       "                                             n_estimators=100, n_jobs=None,\n",
       "                                             oob_score=False, random_state=42,\n",
       "                                             verbose=0, warm_start=False),\n",
       "             iid='deprecated', n_jobs=None,\n",
       "             param_grid=[{'bootstrap': [False, True],\n",
       "                          'max_features': [2, 4, 6, 8],\n",
       "                          'n_estimators': [3, 10, 30]}],\n",
       "             pre_dispatch='2*n_jobs', refit=True, return_train_score=True,\n",
       "             scoring='neg_mean_squared_error', verbose=0)"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "param_grid = [\n",
    "    {'bootstrap':[False, True] ,'n_estimators':[3,10,30], 'max_features' : [2,4,6,8]}\n",
    "]\n",
    "\n",
    "forest_reg = RandomForestRegressor(random_state= 42)\n",
    "grid_search = GridSearchCV(\n",
    "    forest_reg, param_grid, cv = 5, scoring='neg_mean_squared_error',\n",
    "    return_train_score=True)\n",
    "grid_search.fit(housing_final, housing_label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomizedSearchCV(cv=5, error_score=nan,\n",
       "                   estimator=RandomForestRegressor(bootstrap=True,\n",
       "                                                   ccp_alpha=0.0,\n",
       "                                                   criterion='mse',\n",
       "                                                   max_depth=None,\n",
       "                                                   max_features='auto',\n",
       "                                                   max_leaf_nodes=None,\n",
       "                                                   max_samples=None,\n",
       "                                                   min_impurity_decrease=0.0,\n",
       "                                                   min_impurity_split=None,\n",
       "                                                   min_samples_leaf=1,\n",
       "                                                   min_samples_split=2,\n",
       "                                                   min_weight_fraction_leaf=0.0,\n",
       "                                                   n_estimators=100,\n",
       "                                                   n_jobs=None, oob_score=Fals...\n",
       "                                                   warm_start=False),\n",
       "                   iid='deprecated', n_iter=10, n_jobs=None,\n",
       "                   param_distributions={'max_features': <scipy.stats._distn_infrastructure.rv_frozen object at 0x7f47a072ab50>,\n",
       "                                        'n_estimators': <scipy.stats._distn_infrastructure.rv_frozen object at 0x7f479fa7ed00>},\n",
       "                   pre_dispatch='2*n_jobs', random_state=42, refit=True,\n",
       "                   return_train_score=False, scoring='neg_mean_squared_error',\n",
       "                   verbose=0)"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.model_selection import RandomizedSearchCV\n",
    "from scipy.stats import randint \n",
    "param_distribs = {\n",
    "    'n_estimators':randint(low = 1, high = 200),\n",
    "    'max_features':randint(low=1, high = 8)\n",
    "}\n",
    "\n",
    "\n",
    "forest_reg = RandomForestRegressor(random_state= 42)\n",
    "rand_search = RandomizedSearchCV(forest_reg, param_distributions= param_distribs,\n",
    "                               n_iter=10, cv =5, scoring='neg_mean_squared_error',\n",
    "                               random_state = 42)\n",
    "rand_search.fit(housing_final, housing_label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['<1H OCEAN', 'INLAND', 'ISLAND', 'NEAR BAY', 'NEAR OCEAN'],\n",
       "      dtype='<U10')"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "encoder.classes_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "extra_attrs = ['room_per_household','population_per_household','bedrooms_per_room']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([7.73806871e-02, 7.08567341e-02, 3.96392794e-02, 1.67111390e-02,\n",
       "       1.62882611e-02, 1.63389973e-02, 1.48411978e-02, 3.36679205e-01,\n",
       "       4.69441068e-02, 8.01700723e-02, 1.03596876e-01, 1.72108072e-02,\n",
       "       1.54905345e-01, 1.82667321e-04, 3.11942838e-03, 5.13519638e-03])"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid_search.best_estimator_.feature_importances_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['longitude',\n",
       " 'latitude',\n",
       " 'housing_median_age',\n",
       " 'total_rooms',\n",
       " 'total_bedrooms',\n",
       " 'population',\n",
       " 'households',\n",
       " 'median_income',\n",
       " 'median_house_value',\n",
       " 'income_cat',\n",
       " 'room_per_household',\n",
       " 'population_per_household',\n",
       " 'bedrooms_per_room',\n",
       " '<1H OCEAN',\n",
       " 'INLAND',\n",
       " 'ISLAND',\n",
       " 'NEAR BAY',\n",
       " 'NEAR OCEAN']"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_attrs = num_attrs + extra_attrs + list(encoder.classes_)\n",
    "final_attrs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.33667920460944256, 'median_income'),\n",
       " (0.15490534523691032, 'bedrooms_per_room'),\n",
       " (0.10359687613634348, 'room_per_household'),\n",
       " (0.08017007228127458, 'income_cat'),\n",
       " (0.07738068706621438, 'longitude'),\n",
       " (0.07085673408007324, 'latitude'),\n",
       " (0.04694410678509501, 'median_house_value'),\n",
       " (0.03963927938393746, 'housing_median_age'),\n",
       " (0.017210807185837444, 'population_per_household'),\n",
       " (0.016711138976163553, 'total_rooms'),\n",
       " (0.01633899725935047, 'population'),\n",
       " (0.016288261092381472, 'total_bedrooms'),\n",
       " (0.014841197825946654, 'households'),\n",
       " (0.005135196378020746, 'ISLAND'),\n",
       " (0.0031194283818393714, 'INLAND'),\n",
       " (0.0001826673211692604, '<1H OCEAN')]"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# side effects in names\n",
    "sorted(list(zip(grid_search.best_estimator_.feature_importances_,final_attrs )), reverse= True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('longitude', 0.07738068706621438),\n",
       " ('latitude', 0.07085673408007324),\n",
       " ('housing_median_age', 0.03963927938393746),\n",
       " ('total_rooms', 0.016711138976163553),\n",
       " ('total_bedrooms', 0.016288261092381472),\n",
       " ('population', 0.01633899725935047),\n",
       " ('households', 0.014841197825946654),\n",
       " ('median_income', 0.33667920460944256),\n",
       " ('median_house_value', 0.04694410678509501),\n",
       " ('income_cat', 0.08017007228127458),\n",
       " ('room_per_household', 0.10359687613634348),\n",
       " ('population_per_household', 0.017210807185837444),\n",
       " ('bedrooms_per_room', 0.15490534523691032),\n",
       " ('<1H OCEAN', 0.0001826673211692604),\n",
       " ('INLAND', 0.0031194283818393714),\n",
       " ('ISLAND', 0.005135196378020746)]"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(zip(final_attrs, grid_search.best_estimator_.feature_importances_))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_models = grid_search.best_estimator_\n",
    "\n",
    "X_test = test_set.drop('median_house_value', axis = 1)\n",
    "y = test_set['median_house_value'].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_test_final = full_pipeline.transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "48583.02184975061"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sqrt(mean_squared_error(final_models.predict(X_test_final), y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method BaseEstimator.get_params of RandomForestRegressor(bootstrap=False, ccp_alpha=0.0, criterion='mse',\n",
       "                      max_depth=None, max_features=6, max_leaf_nodes=None,\n",
       "                      max_samples=None, min_impurity_decrease=0.0,\n",
       "                      min_impurity_split=None, min_samples_leaf=1,\n",
       "                      min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
       "                      n_estimators=30, n_jobs=None, oob_score=False,\n",
       "                      random_state=42, verbose=0, warm_start=False)>"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid_search.best_estimator_.get_params"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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